Teses / dissertações sobre o tema "Powertrain control"

The transmission is probably the drivetrain component with the greatest impact on driveability of an automatic transmission equipped vehicle. Since the driver only has an indirect influence on the gear shift timing, except for situations like kick-down accelerations, it is desirable to improve shift quality as perceived by the driver. However, improving shift quality is a problem normally diametrically opposed to minimizing transmission clutch energy dissipation. The latter has a great impact on transmission lifetime, and has to be defined and taken into consideration along with the notion of shift quality. The main focus of this thesis is the modeling of a drivetrain of an automatic transmission vehicle, and the implementation in MatLab/Simulink, including the first to second gear upshift. The resulting plant based on the derived equations is validated using data from a test vehicle equipped with a torque sensor located at the transmission output shaft. The shaft torque is more or less proportional to the driveline jerk, and hence of great interest for control purposes. Control strategies are discussed and a PID controller structure is developed to control the first to second gear upshift, as opposed to the traditional open-loop upshift control. Furthermore, the proposed controller structure uses the transmission output torque and the differential speed of the engaging clutch as inputs, to control the clutch pressure and the engine output torque, respectively. The structure is unsophisticated and transparent compared to other approaches, but shows great theoretical results in terms of improved shift quality and decreased clutch wear.

För att ett fordon ska kunna bromsa, accelerera och svänga är friktion mellan däcken och vägen ett måste. Vid för mycket gaspådrag under en acceleration kan det hända att hjulen förlorar fäste och börjar spinna loss, något som leder till både försämrad kontroll över fordonet och att däcken slits ut i förtid. Traction controlsystemet förhindrar hjulen från att spinna loss och försöker maximera friktionen.

Målet med detta examensarbete är att utvärdera olika reglerprinciper samt att undersöka olika möjligheter för att reglera friktionen mellan däck och väg. Det är ett svårt reglerproblem, dels på grund av dess olinjäritet, dels på grund av det faktum att friktionen är en okänd parameter.

För att kunna undersöka olika reglermöjligheter har en modell över hjuldynamiken och en modell över drivlinan tagits fram i Matlabs simuleringsprogram Simulink. Därutöver har tre regulatorer designats: en fuzzy-regulator, en fuzzy-P-regulator och en PI-regulator. Regulatorerna utvärderades i tre tester som bland annat testade deras robusthet.

Fuzzy-regulatorn och fuzzy-P-regulatorn lyckades reglera systemet bra. PI-regulatorn gjorde däremot inte ett tillfredsställande jobb, mest på grund av dess behov av ett börvärde.

Traction is necessary for a vehicle to be able to brake, accelerate and turn. When pushing the accelerator pedal too hard during an acceleration, the wheel can loose traction and start spinning, which leads to a worsen vehicle control and also wears out the tyres faster. The traction control system prevents the wheels from spinning and tries to make the tyres maintain maximum traction.

The purpose of this master’s thesis is to evaluate different control methods and to investigate possible ways to control the traction. This is a difficult control problem due to its nonlinearity and the fact that the friction is an unknown parameter.

For the investigation, a model of the wheel dynamics and a model of the powertrain have been developed in Matlab’s simulation program Simulink. Furthermore, three different controllers have been designed; a fuzzy controller, a fuzzy-P controller and a PI controller. The controllers were evaluated in three test cycles that among others tested their robustness.

The fuzzy controller and the fuzzy-P controller managed to control the system very well. The PI controller, however, did not work satisfactory, mainly because of its need of a desired value.

Optimal Control (OC) is essentially a mathematical extremal problem. The procedure consists on the definition of a criterion to minimize (or maximize), some constraints that must be fulfilled and boundary conditions or disturbances affecting to the system behavior. The OC theory supplies methods to derive a control trajectory that minimizes (or maximizes) that criterion. This dissertation addresses the application of OC to automotive control problems at the powertrain level, with emphasis on the internal combustion engine. The necessary tools are an optimization method and a mathematical representation of the powertrain. Thus, the OC theory is reviewed with a quantitative analysis of the advantages and drawbacks of the three optimization methods available in literature: dynamic programming, Pontryagin minimum principle and direct methods. Implementation algorithms for these three methods are developed and described in detail. In addition to that, an experimentally validated dynamic powertrain model is developed, comprising longitudinal vehicle dynamics, electrical motor and battery models, and a mean value engine model. OC can be utilized for three different purposes: 1. Applied control, when all boundaries can be accurately defined. The engine control is addressed with this approach assuming that a the driving cycle is known in advance, translating into a large mathematical problem. Two specific cases are studied: the management of a dual-loop EGR system, and the full control of engine actuators, namely fueling rate, SOI, EGR and VGT settings. 2. Derivation of near-optimal control rules, to be used if some disturbances are unknown. In this context, cycle-specific engine calibrations calculation, and a stochastic feedback control for power-split management in hybrid vehicles are analyzed. 3. Use of OC trajectories as a benchmark or base line to improve the system design and efficiency with an objective criterion. OC is used to optimize the heat release law of a diesel engine and to size a hybrid powertrain with a further cost analysis. OC strategies have been applied experimentally in the works related to the internal combustion engine, showing significant improvements but non-negligible difficulties, which are analyzed and discussed. The methods developed in this dissertation are general and can be extended to other criteria if appropriate models are available.
El Control Óptimo (CO) es esencialmente un problema matemático de búsqueda de extremos, consistente en la definición de un criterio a minimizar (o maximizar), restricciones que deben satisfacerse y condiciones de contorno que afectan al sistema. La teoría de CO ofrece métodos para derivar una trayectoria de control que minimiza (o maximiza) ese criterio. Esta Tesis trata la aplicación del CO en automoción, y especialmente en el motor de combustión interna. Las herramientas necesarias son un método de optimización y una representación matemática de la planta motriz. Para ello, se realiza un análisis cuantitativo de las ventajas e inconvenientes de los tres métodos de optimización existentes en la literatura: programación dinámica, principio mínimo de Pontryagin y métodos directos. Se desarrollan y describen los algoritmos para implementar estos métodos así como un modelo de planta motriz, validado experimentalmente, que incluye la dinámica longitudinal del vehículo, modelos para el motor eléctrico y las baterías, y un modelo de motor de combustión de valores medios. El CO puede utilizarse para tres objetivos distintos: 1. Control aplicado, en caso de que las condiciones de contorno estén definidas. Puede aplicarse al control del motor de combustión para un ciclo de conducción dado, traduciéndose en un problema matemático de grandes dimensiones. Se estudian dos casos particulares: la gestión de un sistema de EGR de doble lazo, y el control completo del motor, en particular de las consignas de inyección, SOI, EGR y VGT. 2. Obtención de reglas de control cuasi-óptimas, aplicables en casos en los que no todas las perturbaciones se conocen. A este respecto, se analizan el cálculo de calibraciones de motor específicas para un ciclo, y la gestión energética de un vehículo híbrido mediante un control estocástico en bucle cerrado. 3. Empleo de trayectorias de CO como comparativa o referencia para tareas de diseño y mejora, ofreciendo un criterio objetivo. La ley de combustión así como el dimensionado de una planta motriz híbrida se optimizan mediante el uso de CO. Las estrategias de CO han sido aplicadas experimentalmente en los trabajos referentes al motor de combustión, poniendo de manifiesto sus ventajas sustanciales, pero también analizando dificultades y líneas de actuación para superarlas. Los métodos desarrollados en esta Tesis Doctoral son generales y aplicables a otros criterios si se dispone de los modelos adecuados.
El Control Òptim (CO) és essencialment un problema matemàtic de cerca d'extrems, que consisteix en la definició d'un criteri a minimitzar (o maximitzar), restriccions que es deuen satisfer i condicions de contorn que afecten el sistema. La teoria de CO ofereix mètodes per a derivar una trajectòria de control que minimitza (o maximitza) aquest criteri. Aquesta Tesi tracta l'aplicació del CO en automoció i especialment al motor de combustió interna. Les ferramentes necessàries són un mètode d'optimització i una representació matemàtica de la planta motriu. Per a això, es realitza una anàlisi quantitatiu dels avantatges i inconvenients dels tres mètodes d'optimització existents a la literatura: programació dinàmica, principi mínim de Pontryagin i mètodes directes. Es desenvolupen i descriuen els algoritmes per a implementar aquests mètodes així com un model de planta motriu, validat experimentalment, que inclou la dinàmica longitudinal del vehicle, models per al motor elèctric i les bateries, i un model de motor de combustió de valors mitjans. El CO es pot utilitzar per a tres objectius diferents: 1. Control aplicat, en cas que les condicions de contorn estiguen definides. Es pot aplicar al control del motor de combustió per a un cicle de conducció particular, traduint-se en un problema matemàtic de grans dimensions. S'estudien dos casos particulars: la gestió d'un sistema d'EGR de doble llaç, i el control complet del motor, particularment de les consignes d'injecció, SOI, EGR i VGT. 2. Obtenció de regles de control quasi-òptimes, aplicables als casos on no totes les pertorbacions són conegudes. A aquest respecte, s'analitzen el càlcul de calibratges específics de motor per a un cicle, i la gestió energètica d'un vehicle híbrid mitjançant un control estocàstic en bucle tancat. 3. Utilització de trajectòries de CO com comparativa o referència per a tasques de disseny i millora, oferint un criteri objectiu. La llei de combustió així com el dimensionament d'una planta motriu híbrida s'optimitzen mitjançant l'ús de CO. Les estratègies de CO han sigut aplicades experimentalment als treballs referents al motor de combustió, manifestant els seus substancials avantatges, però també analitzant dificultats i línies d'actuació per superar-les. Els mètodes desenvolupats a aquesta Tesi Doctoral són generals i aplicables a uns altres criteris si es disposen dels models adequats.
Reig Bernad, A. (2017). Optimal Control for Automotive Powertrain Applications [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90624
TESIS

In this thesis an integrated powertrain control for gearshifts on twin clutch transmissions is developed. First, a detailed model of an automotive powertrain featuring a twin clutch transmission is developed in Matlab/Simulink®. This model includes detailed friction models for the twin clutch that enable an investigation into the effects of different friction materials on the performance of the gearshift controller. The transmission model also includes detailed models of the synchronisers and thus allows a simulation of synchroniser-to-synchroniser shifts. A simplified phenomenological model, derived from a more complex non-linear model, is employed to model the hydraulic actuation of clutches and synchroniser. The thesis finds that the dependency of the friction coefficient on the sliding speed has an important influence on the gearshift quality and the performance of gearshift controller, while the absolute level of the friction coefficient is less important. Based on this powertrain model the key problems of gearshifts on twin clutch transmissions were identified and a control that overcomes these problems was developed. The first stage was to devise a gearshift control algorithm that handles single clutch-to-clutch shifts without a oneway (freewheeler-, overrunning-) clutch. This basic gearshift control algorithm featured a control of clutch slip for the engine torque transfer and a control of engine speed through engine torque manipulation (plus clutch pressure manipulation for downshifts). In a second stage, an optional transmission output torque control was developed that could be integrated in the basic control. The thesis shows that these control strategies are superior, in terms of shift quality, to conventional gearshift controls as used on planetary-type transmissions and are also robust against variations in the powertrain parameters (including friction coefficient) and sensor noise. The control strategies developed for single clutch-to-clutch shifts were extended to handle double and other multiple gearshifts that take place in the same transmission half. The thesis also investigates the other main part of gearshifts on twin clutch transmissions, the gear pre-selection. The thesis shows that, on power-on gearshifts, the torque reactions at the transmission output due to the gear pre-selection with conventional hydraulically actuated synchronisers can be effectively compensated for by a simple manipulation of engine torque.

The torque dynamic caused by the firing pulse from diesel engines set high robustness demands for gearboxes and final drives in today’s heavy duty trucks. If these dynamic loads could be eliminated or dampened, the driveline can be built lighter because of the lower demands which in turn would save fuel for the driver and material cost for the manufacturer. There exist solutions to this problem that include expensive and complicated hardware; for example the double mass flywheel, but there is one opportunity that is potentially for free to the manufacturer, namely clutch slip control. The hypothesis of this thesis is that the torque oscillations from the engine can be reduced by controlling the clutch slip velocity. It is also evaluated if it is possible to control a slip using existing hardware in a Scania powertrain and if the control performance can be improved by changing one of the powertrain parameters. For the scope of this thesis, the wear rate and temperature of the clutch when slipping is not considered. The first step of the thesis is to construct a MBS model of the powertrain in question. Further on, two control designs, namely fuzzy control and two degrees of freedom control are implemented using model based control design. Both control algorithms are implemented in a heavy duty truck and the performance is evaluated. To find the parameter that constrains the performance, a parameter variation is performed using the developed model to save both time and cost. It is proved that the torque dynamics from the diesel engine can be dampened by forty to eighty percent in amplitude by slipping the clutch and that the implemented control design gives acceptable results for gears seven to twelve using existing hardware. The parameter variation shows that the actuation delay is the main limiting factor, enabling stable control at the first gear if removed completely. The slip control concept shows potential but sets high demands for hardware specification, especially for actuation delays if all gears are to be used with slip control. Using existing hardware, the control is fully implementable for gears seven to twelve with good results.
Det dynamiska momentet som tändpulserna ger upphov till i dieselmotorer ställer höga krav på robusthet och hållfasthet hos växellådor och slutväxlar i lastbilar. Om dynamiken kunde elimineras eller dämpas ut vore det möjligt att bygga transmissionen lättare eftersom kraven på robusthet och hållfasthet skulle minska. Detta skulle i slutändan betyda lägre bränsleförbrukning för åkeriet och lägre materialkostnader för lastbilstillverkaren. I dagsläget finns det flera dyra lösningar som bygger på komplicerade mekaniska koncept, däribland dubbelmassesvänghjulet, men det finns en möjlighet som potentiellt är gratis för tillverkaren ur ett materialperspektiv, nämligen kopplingsslirkontroll. Hypotesen i det här examensarbetet är att momentoscillationerna från motorn kan reduceras genom att kontrollera slirhastigheten i kopplingen. Det utvärderas också om det är möjligt att kontrollera slirhastigheten genom att använda komponenterna i en befintlig, produktionssatt Scania drivlina och om det finns en nyckelparameter i hårdvaran som tydligt begränsar regleringens prestanda. Kopplingens temperatur och slitning anses vara utanför ramen för detta examensarbete och behandlas inte i denna rapport. Som första steg i utvecklingen konstrueras en MBS-modell av drivlinan i fråga. Fortsättningsvis implementeras två reglerstrukturer, nämligen fuzzy-reglering och tvåfrihetsgradsreglering genom att använda modellbaserad utveckling. För att utreda prestandan i dagens system implementeras båda reglerstrukturerna i en lastbil där verklig provning utförs. För att hitta den begränsande faktorn utförs en parametervariation i den utvecklade modellen istället för i en lastbil, vilket sparar både tid och minskar kostnaden. I det här examensarbetet har det visats att momentdynamiken från dieselmotorn kan dämpas ut med fyrtio till åttio procent i amplitud genom att slira på kopplingen och att den implementerade reglering ger en acceptabel prestanda för växlarna sju till tolv i existerande hårdvara. Den utförda parametervariationen visar att fördröjningen mellan beräknad styrsignal och faktisk aktuering är mest begränsande och att en eliminering av denna möjliggör stabil reglering på första växeln. Kopplingsslirregleringskonceptet visar stor potential men sätter höga krav på hårdvara; inte minst aktueringsfördröjningen om regleringen ska användas på alla växlar. Med existerande drivlina är dock regleringen fullt implementerbar sju till och med tolv.

The torque dynamic caused by the firing pulse from diesel engines set high robustness demands for gearboxes and final drives in today’s heavy duty trucks. If these dynamic loads could be eliminated or dampened, the driveline can be built lighter because of the lower demands which in turn would save fuel for the driver and material cost for the manufacturer. There exist solutions to this problem that include expensive and complicated hardware; for example the double mass flywheel, but there is one opportunity that is potentially for free to the manufacturer, namely clutch slip control. The hypothesis of this thesis is that the torque oscillations from the engine can be reduced by controlling the clutch slip velocity. It is also evaluated if it is possible to control a slip using existing hardware in a Scania powertrain and if the control performance can be improved by changing one of the powertrain parameters. For the scope of this thesis, the wear rate and temperature of the clutch when slipping is not considered. The first step of the thesis is to construct a MBS model of the powertrain in question. Further on, two control designs, namely fuzzy control and two degrees of freedom control are implemented using model based control design. Both control algorithms are implemented in a heavy duty truck and the performance is evaluated. To find the parameter that constrains the performance, a parameter variation is performed using the developed model to save both time and cost. It is proved that the torque dynamics from the diesel engine can be dampened by forty to eighty percent in amplitude by slipping the clutch and that the implemented control design gives acceptable results for gears seven to twelve using existing hardware. The parameter variation shows that the actuation delay is the main limiting factor, enabling stable control at the first gear if removed completely. The slip control concept shows potential but sets high demands for hardware specification, especially for actuation delays if all gears are to be used with slip control. Using existing hardware, the control is fully implementable for gears seven to twelve with good results.
Det dynamiska momentet som tändpulserna ger upphov till i dieselmotorer ställer höga krav på robusthet och hållfasthet hos växellådor och slutväxlar i lastbilar. Om dynamiken kunde elimineras eller dämpas ut vore det möjligt att bygga transmissionen lättare eftersom kraven på robusthet och hållfasthet skulle minska. Detta skulle i slutändan betyda lägre bränsleförbrukning för åkeriet och lägre materialkostnader för lastbilstillverkaren. I dagsläget finns det flera dyra lösningar som bygger på komplicerade mekaniska koncept, däribland dubbelmassesvänghjulet, men det finns en möjlighet som potentiellt är gratis för tillverkaren ur ett materialperspektiv, nämligen kopplingsslirkontroll. Hypotesen i det här examensarbetet är att momentoscillationerna från motorn kan reduceras genom att kontrollera slirhastigheten i kopplingen. Det utvärderas också om det är möjligt att kontrollera slirhastigheten genom att använda komponenterna i en befintlig, produktionssatt Scania drivlina och om det finns en nyckelparameter i hårdvaran som tydligt begränsar regleringens prestanda. Kopplingens temperatur och slitning anses vara utanför ramen för detta examensarbete och behandlas inte i denna rapport. Som första steg i utvecklingen konstrueras en MBS-modell av drivlinan i fråga. Fortsättningsvis implementeras två reglerstrukturer, nämligen fuzzy-reglering och tvåfrihetsgradsreglering genom att använda modellbaserad utveckling. För att utreda prestandan i dagens system implementeras båda reglerstrukturerna i en lastbil där verklig provning utförs. För att hitta den begränsande faktorn utförs en parametervariation i den utvecklade modellen istället för i en lastbil, vilket sparar både tid och minskar kostnaden. I det här examensarbetet har det visats att momentdynamiken från dieselmotorn kan dämpas ut med fyrtio till åttio procent i amplitud genom att slira på kopplingen och att den implementerade reglering ger en acceptabel prestanda för växlarna sju till tolv i existerande hårdvara. Den utförda parametervariationen visar att fördröjningen mellan beräknad styrsignal och faktisk aktuering är mest begränsande och att en eliminering av denna möjliggör stabil reglering på första växeln. Kopplingsslirregleringskonceptet visar stor potential men sätter höga krav på hårdvara; inte minst aktueringsfördröjningen om regleringen ska användas på alla växlar. Med existerande drivlina är dock regleringen fullt implementerbar sju till och med tolv.

In order to meet increasingly strict regulations on vehicle emissions, manufacturers are seeking ways to produce vehicles that emit less pollution and consume less fuel. Eco-driving is the optimisation of velocity and gear selection in existing vehicles to reduce fuel consumption and such reductions can be made at relatively low development costs compared to powertrain modification. However, the driving experience of a premium vehicle could be compromised if the vehicle behaviour differs from that which is expected by the driver and the acceptance of such fuel saving measures may be diminished. Therefore, in order to maintain the driving experience the contribution of this work is the development and implementation of an optimal control algorithm based on Dynamic Programming which optimises, in real time, the vehicle velocity and gear selection based on a vehicle and upcoming road model while consideration is given to objective measures of driveability. The algorithm is deployed on a Raspberry Pi miniature computer with connection to the vehicle data network. Fuel savings and time savings are identified with the optimisation algorithm both with and without violating constraints on driveability, first in simulation and finally in a real-time, in-vehicle eco-driving feedback system. Primarily the application of this system is in internal combustion engine passenger vehicles in both urban and extra-urban road situations, however the approach is deliberately flexible to allow development for other powertrain configurations.

This thesis develops and investigates the application of novel identification and structure identification techniques for I.C. engine systems. The legislated demand for reduced vehicle fuel consumption and emissions indicates that improved model-based dynamical engine calibration and control methods are required in place of the existing static set-point based mapping methods currently used in industry. The choice of structure of any dynamical engine model has significant consequences for the accuracy and the calibration/optimization time of engine systems. This thesis primarily addresses the issue of this structure selection. Linear models are well understood and relatively easy to implement however the modern I.C. engine is a highly nonlinear system which restricts the use of linear structures. Further the newer technologies required to achieve demanding fuel consumption and emission targets are increasingly more complex and nonlinear. The selection of appropriate nonlinear model regressor terms presents a combinatorial explosion problem which must be solved for accurate engine system modelling. In this thesis, two systematic nonlinear model structure selection techniques, namely stepwise regression with F-statistics and orthogonal least squares method with error reduction ratio, are accordingly investigated. SISO algebraic NARMAX engine models are then established in simulation studies with these methods and demonstrate the effectiveness of the approach. The thesis also investigates the development and application of multi-modelling techniques and the expansion of the model structure selection techniques to the identification of the local models terms within the multi-model structures for the engine. Based on the en- gine operating regions, novel multi-model networks can be established and several alternative multi-modelling techniques, such as LOLIMOT, Neural Network, Gaussian and log-sigmoid function weighted multi-models, for the multi-model engine system identification are explored and compared. An experimental validation of the methods is given by a black box identification of SISO engine models which are developed purely from the experimental engine test data sets. The results demonstrate that the multi-model structure selection techniques can be successfully applied on the engine systems, and that the multi-modelling techniques give good model accuracy and that good modelling efficiency can also be achieved. The outcome is a set of techniques for the efficient development of accurate nonlinear black-box models which can be acquired from experimental dynamometer test-bed data which should assist in the dynamic control of future advanced technology engine systems.

Powertrain applications require high performance controllers yet are in general restricted to low order solutions due to limitations in the software and hardware. There are many well developed robust feedback techniques which can be applied very successfully to automotive systems, however these are generally high order solutions and are therefore not suited to most commercial powertrain control modules (PCM). Typically, powertrain control strategies are implemented through low order look-up tables. There are only a limited number of robust design methods which can be used for fixed, low order controller design and many of these techniques are limited to single-input-single-output (SISO) problems. New technology engines are being developed with additional mechanical systems to increase the performance. As these technologies are developed the interactions between system inputs and outputs are increasingly coupled and therefore it is necessary to consider engines .as multivariable systems. Accordingly, for high performance control it is necessary to move away from single control loops or sequential SISO loop designs favoured until recently. To achieve high performance with the constraints of the PCM this thesis develops a series of 'engineer friendly' controller design tools. Two distinct parameter space (PS) control techniques are detailed, which are particularly suited to low and fixed order control. These methodologies are intended to be suitable for non-control experts by offering insights into the design constraints. The first technique is a novel PS approach to constrained and minimum variance (MV) controller design for both continuous and discrete systems. This technique is successfully applied to the peak pressure position (PPP) control problem using spark advance (SA) as the input. The second technique developed is a multivariable 'Hoc parameter space technique for designing fixed, low order controllers. This technique uses only frequency response information in the design scheme and is therefore equally suited to both continuous and discrete systems. Controllers are developed by a series of parameter plane iterations, which can be used for re-tuning controllers from alternative design methods. Equally, the technique can be used for the direct design of controllers, starting with no initial transfer function gains. The method is successfully demonstrated as a direct design technique for a single sensitivity problem with time response criteria. A further example demonstrates the technique for weighted sensitivity reduction using the direct design approach and also for re-tuning a reduced order controller obtained by an algebraic Riccati design. To facilitate the application of the multivariable PS technique, a novel approach to designing a feedforward fuelling controller for a port fuel injection (PFI) gasoline engine is detailed. The feedforward controller is based on inverse nonlinear auto-regressive moving average (NARMA) ordina.ry least squares (OLS) identification. The approach is applied successfully to the idle speed region of an engine and has the advantage on linearising the plant dynamics. The system with compensator is subsequently re-identified and coupled with a robust multivariable PS controller for control of the idle speed and air-to-fuel ratio (AFR).

L’application de quotas d’émissions de gaz à effet de serre a amené les constructeurs automobiles à augmenter le niveau d’électrification de leurs véhicules. En parallèle des véhicules tout électrique, se sont développées les solutions hybrides, tel le mild-hybrid autorisant l’association d’une chaîne de traction électrique avec le moteur à combustion dans le but d’absorber les pics de consommation de carburant. Afin de rester compétitif, les coûts de production d’un véhicule doivent être optimisés autant que possible, ainsi l’étude réalisée de commande de machine synchrone à griffes sans capteur de courant permet la suppression des capteurs du stator de la machine et donc de s’affranchir de leur coût. Une commande vectorielle de la machine est nécessaire afin d’optimiser les courants statoriques pour un couple donné. L’utilisation d’observateurs d’état permettant l’estimation des courants manquants a donc été privilégiée. Ainsi différentes topologies d’observateurs ont été développées : le filtre de Kalman étendu ainsi qu’un observateur d’état et deux déclinaisons dont la conception est basée sur une analyse de convergence à l'aide de fonctions de Lyapunov. Afin d’améliorer la précision de l’observation des courants statoriques, une étude approfondie du modèle électrique de la machine a été réalisée. Elle permet de minimiser les erreurs dues aux variations paramétriques, liées notamment à la saturation magnétique de la machine et des incertitudes liées aux phénomènes non modélisés de la chaîne de conversion électromécanique. Une méthode de cartographie de la machine a ainsi été proposée à l’aide d’un estimateur paramétrique. Les résultats expérimentaux, obtenus sur un banc de test réalisé en laboratoire, sont concluants en régime établi : les courants non mesurés sont estimés avec une précision satisfaisante pour une application automobile et permettent le contrôle sans capteur de courant de la machine
The application of greenhouse gases quotas has led the automotive manufacturers to increase the electrification level of their vehicles. In parallel with Battery Electric Vehicles (BEV), hybridization solutions have been developed. Among them, mild-hybrid technology allows the connection of an electric powertrain with an Internal Combustion Engine (ICE) with the aim of absorbing peaks of fuel consumption. In order to remain competitive, the manufacturing costs of a vehicle need to be optimized. In that regard, removing the stator currents sensors allows avoiding their inherent costs. However, within the vector control framework, a feedback on these currents is required to optimize their value for a given torque. For this reason, it has been decided to use state observers to estimate the missing currents. Different state observer solutions have thus been developed: the Extended Kalman Filter (EKF) and a state observer with two extensions whose design is based on a convergence analysis using Lyapunov functions. With the aim of improving the precision of the stator currents estimation, an in-depth study of the machine's electrical model was carried out. It allows minimizing errors due to parametric variations, related in particular to the magnetic saturation of the machine and uncertainties due to unmodeled phenomena in the whole drive. A method for mapping the machine was proposed using a parametric estimator. The experimental results, obtained on a test bench built in the laboratory, are conclusive in steady-state: the real currents are estimated with a satisfying precision for an automotive application and allow performing a current sensorless control of the machine

This degree project work has been carried out in the context of in the Hybrid InnovativePowertrain (HIP) project presently executed by the company Altran Technologies S.A.. Itspurpose is to provide clients with a modular platform to model and simulate their vehicleas accurately and as fast as possible. The idea is to build a custom Simulink library with ablock for each major component found in any road vehicle. The platform must enable clientsto model battery electric vehicle as well as plug-in hybrid or fuel cell vehicles with differentpowertrain topologies. It must provides component blocks for each layer of control, fromhigh-level energy efficiency algorithms embedded in high authority hardware to low-levelcomponent control solutions.The work presented here contributes to the development of the modular powertrain electricpart with the electric motor, the inverter and the chopper. It is composed of three mainsteps :• Building an electric powertrain model with its proper control schemes in order to enablefast simulations. The model must be split into blocks that become part of the projectlibrary.• Building a more realistic model that takes into account the discontinuous switchingdynamics and the discrete nature of the actual controllers, in order to verify andvalidate the control effectiveness• Designing a diagnostic method for inverter faultsThe first part of this work is dedicated to a literature review of automotive electric drivessolutions as well as the research in progress in the domain, notably in fault detection schemes.The mathematical models and controller designs used for the simulations are developed in asecond part. The last part presents the software implementation aspects and the analysedsimulation results.
Detta examensarbete har utförts inom ramen för det så kallade Hybrid Innovative Powertrain(HIP)-projectet vid företaget Altran. Syftet med arbetet har varit att kunna förseolika klienter med en modulär plattform för att kunna modellera och elfordon så noggrantoch snabbt som möjligt. Huvudidén har varit att ta fram ett modellbibliotek i Simulink representerandenyckelkomponenterna i ett vägfordon. Plattformen möjliggör modellerandetav helelektriska fordon samt även plug-in hybridfordon och bränsecellsdrivna fordon. Inomramen för detta examensarbete har elmotor, omriktare samt dc-dc-omvandlare modellerats.Modeller både inkluderande och exkluderande kraftelektronikens (antaget ideala) switchförlopphar tagits fram. Modellen inkluderande switchförlopp har även använts för att studeraen metodik för att diagnostisera omriktarfel. Första delen av examensarbetet presenteraren litteraturundersökning med särskilt fokus på metoder för feldetektering. Matematiskamodeller och regulatordesign beskrivs i arbetets andra del. Arbetets sista del beskrivermjukvaruimplementeringen samt analyserar de erhållna simuleringsresultaten.

This thesis is providing an insight into the verification of a quasi-static simulation model based on the estimation of fuel consumption using machine learning methods. Traditional verification using real test data is not always available. Therefore, a methodology consisting of verification analysis based on estimation methods was developed together with an improving process of a quasi-static simulation model. The modelling of the simulation model mainly consists of designing and implementing a gear selection strategy together with the gearbox itself for a dual clutch transmission dedicated to hybrid application. The purpose of the simulation model is to replicate the fuel consumption behaviour of vehicle data provided from performed tests. To verify the simulation results, a so-called ranking model is developed. The ranking model estimates a fuel consumption reference for each time step of the WLTC homologation drive cycle using multiple linear regression. The results of the simulation model are verified, and a scoring system is used to indicate the performance of the simulation model, based on the correlation between estimated- and simulated data of the fuel consumption. The results show that multiple linear regression can be an appropriate approach to use as verification of simulation models. The normalised cross-correlation power is also examined and turns out to be a useful measure for correlation be-tween signals including a lag. The developed ranking model is a fast first step of evaluating a new vehicle configuration concept.

The automotive industry is faced with the challenge of ever-increasing emission legislation. This study demonstrates the effective use of nonlin­ear techniques in automotive control for the problem of fuel and emission minimisation. A review of previous work highlights the inadequacy of traditional optimisation formulations. The conflicting requirements of both low fuel and emissions is a design problem for which compromise and trade-offs are unavoidable. This study attacks the problem through powertrain scheduling, an approach ideally suited to both S.I. and diesel engines, and demonstrates how the novel application of multi-objective optimisation methods provides a solution more akin to the real physical problem. The modern control theory approach presented is a three stage pro­cess : formulation of the mathematical model, including the essential dy­namics, constraints, and objectives of the physical problem; optimisation of the control strategy with respect to the relevant performance criteria; and synthesis of the optimal control design. The optimisation model is finite-dimensional and nonlinear, the use of which demands a knowledge of nonlinear systems and available methods. These are classified. Re­sults for single and multi-objective optimisations are compared and fully demonstrate the advantages of the latter for the scheduling problem. Op­timal schedules are generated and from them, implementable rule-based control laws are derived. Performance, in terms of the ability to track a legislative test cycle and to retain the optimal design specification, is demonstrated through dynamic simulation, as is their driveability and robustness. This study specifically considers a diesel-engined vehicle incorporating a CVT. The methods tire widely applicable however, to other engine and transmissions types, and to other automotive control problems.

Driveability is an important issue in the development of modern trucks. Comfort and sense of control are key for the driver. During a gear shift, the flywheel torque is lowered to zero before disengaging the clutch and then increased again after engaging the clutch. Lowering and increasing the flywheel torque creates movements in the cab. The previous developments of the gear shift functionality has had the purpose to maintain a good behaviour in the powertrain. This Master’s thesis has instead investigated whether it was possible to improve the cab comfort during autonomous gear shifts by altering the way it is performed. A measure of cab comfort has been developed through experiments and cooperation a test driver. The main differences between good and bad gear shifts were identified as the amplitudes of cab accelerations and jerk. Therefore, the goal was to minimize acceleration and jerk in order to improve the cab comfort. A model of how the powertrain affects the cab movements has been developed. Sub models of the powertrain, chassis and cab were developed individually and combined into one large model. The models performed well individually and the combined model was judged to be good enough for developing a controller. At the time of writing the existing controller had the purpose of preventing oscillations and jerk in the driveline. To avoid having to consider behaviour in the powertrain the developed controller were to control the existing controller. Two approaches have been investigated, open loop control and feedback control. The functionality of the open loop controller was to low pass filter inputs to the existing controller. The other approach was a feedback controller using the z-acceleration (upwards) as feedback. The purpose was to keep the acceleration low using a reference developed with experience from the comfort experiments. Simulations of the open loop controller showed that it was possible to alter the cab comfort by altering the engine torque. The comfort was improved in most parts of the gear shift and worsend in some parts. The feedback controller showed promising results in simulations. It was problematic to combine the existing controller with the developed controller since they have different purposes. By a fusion of the controllers there would be good opportunities to improve the gearshift with respect to both powertrain behaviour and cab comfort.

A major challenge in the transportation industry is how to reduce the emissions of greenhouse gases. One way of achieving this in vehicles is to drive more fuel-efficiently. One recently developed technique that has been successful in reducing the fuel consumption is the look-ahead cruise controller, which utilizes future conditions such as road topography. In this this thesis, similar methods are used in order to reduce the fuel consumption of heavy-duty vehicles driving in environments where the required and desired velocity vary. The main focus is on vehicles in urban driving, which must alter their velocity due to, for instance, changing legal speed restrictions and the presence of intersections. The driving missions of such vehicles are here formulated as optimal control problems. In order to restrict the vehicle to drive in a way that does not deviate too much from a normal way of driving, constraints on the velocity are imposed based on statistics from real truck operation. In a first approach, the vehicle model is based on forces and the cost function involves the consumed energy. This problem is solved both offline using Pontryagin's maximum principle and online using a model predictive controller with a quadratic program formulation. Simulations show that 7 % energy can be saved without increasing the trip time nor deviating from a normal way of driving. In a second approach, the vehicle model is extended to include an engine and a gearbox with the objective of minimizing the fuel consumption. A fuel map for the engine and a polynomial function for the gearbox losses are extracted from experimental data and used in the model. This problem is solved using dynamic programming taking into consideration gear changes, coasting with gear and coasting in neutral. Simulations show that by allowing the use of coasting in neutral gear, 13 % fuel can be saved without increasing the trip time or deviating from a normal way of driving. Finally, an implementation of a rule-based controller into an advanced vehicle model in highway driving is performed. The controller identifies sections of downhills where fuel can be saved by coasting in neutral gear.
En stor utmaning för transportsektorn är hur utsläppen av växthusgaser ska minskas. Detta kan åstadkommas i fordon genom att köra bränslesnålare. En nyligen utvecklad teknik som har varit framgångsrik i att minska bränsleförbrukningen är framförhållningsreglering, som använder framtida förhållanden så som vägtopografi. I denna avhandling används liknande metoder för att minska bränsleförbrukningen i tunga fordon som kör i miljöer där önskad och tvingad hastighet varierar. Fokus ligger framförallt på fordon i stadskörning, där hastigheten måste varieras beroende på bland annat hastighetsbegränsningar och korsningar. Denna typ av körning formuleras här som optimala reglerproblem. För att hindra fordonet från att avvika för mycket från ett normalt körbeteende sätts begränsningar på tillåten hastighet baserat på statistik från verklig körning. Problemet angrips först genom att använda en fordonsmodell baserad på krafter och en kriteriefunktion innehållande energiförbrukning. Problemet löses både offline med Pontryagin's maximum princip och online med modellprediktiv reglering baserad på kvadratisk programmering. Simuleringar visar att 7 % energi kan sparas utan att öka körtiden eller avvika från ett normalt körbeteende. Problemet angrips sedan genom att utöka fordonsmodellen till att också innehålla motor och växellåda med målet att minimera bränsleförbrukningen. Specifik bränsleförbrukning och en polynomisk approximation av förlusterna i växellådan är extraherade från experiment och används i simuleringarna. Problemet löses genom dynamisk programmering som tar hänsyn till växling, släpning och frirullning. Simuleringar visar att 13 % bränsle kan sparas utan att öka körtid eller avvika från normalt körbeteende genom att tillåta frirullning. Slutligen görs en implementering av en regelbaserad regulator på en avancerad fordonsmodell för ett fordon i motorvägskörning. Regulatorn identifierar sektioner med nedförsbackar där bränsle kan sparas genom frirulllning.

QC 20171011

Increased environmental awareness together with new legislative demands on lowered emissions and a rising fuel cost have put focus on increasing the fuel efficiency in new vehicles. Hybridization is a way to increase the efficiency of the powertrain.The Haldex electric Torque Vectoring Device is a rear axle with a built in electric motor, designed to combine all-wheel drive with hybrid functionality. A method is developed for creating a real time control algorithm that minimizes the fuel consumption. First the consumption reduction potential of the system is investigated using Dynamic Programming. A real time control algorithm is then devised that indicates a substantial consumption reduction potential compared to all-wheel drive, under the condition that the assumed and measured efficiencies are accurate. The control algorithm is created using equivalent consumption minimization strategy and is implemented without any knowledge of the future driving mission. Two ways of adapting the control according to the battery state of charge are proposed and investigated. The controller optimizes the torque distribution for the current gear as well as assists the driver by recommending the gear which would give the lowest consumption. The simulations indicate a substantial fuel consumption reduction potential even though the system primarily is an all-wheel drive concept. The results from vehicle tests show that the control system is charge sustaining and the driveability is deemed good by the test-drivers.

Heavy duty powertrains are complex systems with components from various domains, different response times during transient operations and different efficient operating ranges. To ensure efficient transient operation of a powertrain, e.g. with low fuel consumption or short transient duration, it is important to come up with proper control strategies. In this dissertation, optimal control theory is used to calculate and analyze efficient heavy duty powertrain controls during transient operations in different applications. This is enabled by first developing control ready models, usable for multi-phase optimal control problem formulations, and then using numerical optimal control methods to calculate the optimal transients. Optimal control analysis of a wheel loader operating in a repetitive loading cycle is the first studied application. Increasing fuel efficiency or reducing the operation time in such repetitive loading cycles sums up to large savings over longer periods of time. Load lifting and vehicle traction consume almost all of the power produced by a diesel engine during wheel loader operation. Physical models are developed for these subsystems where the dynamics are described by differential equations. The model parameters are tuned and fuel consumption estimation is validated against measured values from real wheel loader operation. The sensitivity of wheel loader trajectory with respect to constrains such as the angle at which the wheel loader reaches the unloading position is also analyzed. A time and fuel optimal trajectory map is calculated for various unloading positions. Moreover, the importance of simultaneous optimization of wheel loader trajectory and the component transients is shown via a side to side comparison between measured fuel consumption and trajectories versus optimal control results. In another application, optimal control is used to calculate efficient gear shift controls for a heavy duty Automatic Transmission system. A modeling and optimal control framework is developed for a nine speed automatic transmission. Solving optimal control problems using the developed model, time and jerk efficient transient for simultaneous disengagement of off-going and engagement of in-coming shift actuators are obtained and the results are analyzed. Optimal controls of a diesel-electric powertrain during a gear shift in an Automated Manual Transmission system are calculated and analyzed in another application of optimal control. The powertrain model is extended by including driveline backlash angle as an extra state in the system. This is enabled by implementation of smoothing techniques in order to describe backlash dynamics as a single continuous function during all gear shift phases. Optimal controls are also calculated for a diesel-electric powertrain corresponding to a hybrid bus during a tip-in maneuver. It is shown that for optimal control analysis of complex powertrain systems, minimizing only one property such as time pushes the system transients into extreme operating conditions far from what is achievable in real applications. Multi-objective optimal control problem formulations are suggested in order to obtain a compromise between various objectives when analyzing such complex powertrain systems.

Poweitrain systems of increasing complexity are being introduced by automotive manufacturers in order to reduce carbon emissions into the atmosphere: hybrid electric vehicles and continuously variable transmissions represent effective contributions to achieve the emission reduction target. The increased complexity calls for more sophisticated control strategies to be developed; different energy management approaches have been investigated in the past, in most cases without considering driveability requirements. Those strategies relying on the knowledge of future driving conditions cannot be deployed in a real-time controller and are only used to investigate patterns of optimal behaviour. This Thesis investigates two energy management strategies for an innovative parallel hybrid powertrain concept with innately variable transmission. This was developed as part of a government funded research project aiming at demonstrating the potential fuel economy benefit of such driveline configuration. Both strategies have a common architecture and rely on a common scheme to control the transient vehicle response; this was experimentally calibrated in order to provide improved driveability levels with respect to the conventional non hybrid powertrain deploying the same transmission concept. This control scheme and its calibration are maintained across the two energy management strategies so that consistent vehicle behaviour is achieved and the cost of driveability in terms of energy usage is preserved. The first energy management strategy was heuristically formulated to maximise operation of the single powertrain components in conditions of maximum efficiency. Optimal design techniques were adopted for the calibration of the corresponding rule set. The second strategy formulation was based on the analysis of the simulation results obtained from a dynamic programming model; regression analysis techniques were used to provide the necessary knowledge base required for the control rules formulation and calibration. ln both cases engineering intuition is required for the interpretation of the simulation results and for the individuation of patterns of behaviour. The hybrid powertrain provides consistent fuel economy improvements with respect to the equivalent non hybrid powertrain with innately variable transmission. A driveability appraisal was conducted and the subjective ratings showed an improved overall driveability level of the hybrid powertrain. Despite producing different control and state trajectories, both strategies provide similar fuel economy figures across a set of legislative drive cycles thus demonstrating that both approaches effectively exploit the hardware limits of the powertrain plant.

Poweitrain systems of increasing complexity are being introduced by automotive manufacturers in order to reduce carbon emissions into the atmosphere: hybrid electric vehicles and continuously variable transmissions represent effective contributions to achieve the emission reduction target. The increased complexity calls for more sophisticated control strategies to be developed; different energy management approaches have been investigated in the past, in most cases without considering driveability requirements. Those strategies relying on the knowledge of future driving conditions cannot be deployed in a real-time controller and are only used to investigate patterns of optimal behaviour. This Thesis investigates two energy management strategies for an innovative parallel hybrid powertrain concept with innately variable transmission. This was developed as part of a government funded research project aiming at demonstrating the potential fuel economy benefit of such driveline configuration. Both strategies have a common architecture and rely on a common scheme to control the transient vehicle response; this was experimentally calibrated in order to provide improved driveability levels with respect to the conventional non hybrid powertrain deploying the same transmission concept. This control scheme and its calibration are maintained across the two energy management strategies so that consistent vehicle behaviour is achieved and the cost of driveability in terms of energy usage is preserved. The first energy management strategy was heuristically formulated to maximise operation of the single powertrain components in conditions of maximum efficiency. Optimal design techniques were adopted for the calibration of the corresponding rule set. The second strategy formulation was based on the analysis of the simulation results obtained from a dynamic programming model; regression analysis techniques were used to provide the necessary knowledge base required for the control rules formulation and calibration. ln both cases engineering intuition is required for the interpretation of the simulation results and for the individuation of patterns of behaviour. The hybrid powertrain provides consistent fuel economy improvements with respect to the equivalent non hybrid powertrain with innately variable transmission. A driveability appraisal was conducted and the subjective ratings showed an improved overall driveability level of the hybrid powertrain. Despite producing different control and state trajectories, both strategies provide similar fuel economy figures across a set of legislative drive cycles thus demonstrating that both approaches effectively exploit the hardware limits of the powertrain plant.

With the dramatic development of the automotive industry and global economy, the motor vehicle has become an indispensable part of daily life. Because of the intensive competition, vehicle manufacturers are investing a large amount of money and time on research in improving the vehicle performance, reducing fuel consumption and meeting the legislative requirement of environmental protection. Engine calibration is a fundamental process of determining the vehicle performance in diverse working conditions. Control maps are developed in the calibration process which must be conducted across the entire operating region before being implemented in the engine control unit to regulate engine parameters at the different operating points. The traditional calibration method is based on steady-state (pseudo-static) experiments on the engine. The primary challenge for the process is the testing and optimisation time that each increases exponentially with additional calibration parameters and control objectives. This thesis presents a basic dynamic black-box model-based calibration method for multivariable control and the method is applied experimentally on a gasoline turbocharged direct injection (GTDI) 2.0L virtual engine. Firstly the engine is characterized by dynamic models. A constrained numerical optimization of fuel consumption is conducted on the models and the optimal data is thus obtained and validated on the virtual system to ensure the accuracy of the models. A dynamic optimization is presented in which the entire data sequence is divided into segments then optimized separately in order to enhance the computational efficiency. A dynamic map is identified using the inverse optimal behaviour. The map is shown to be capable of providing a minimized fuel consumption and generally meeting the demands of engine torque and air-fuel-ratio. The control performance of this feedforward map is further improved by the addition of a closed loop controller. An open loop compensator for torque control and a Smith predictor for air-fuel-ratio control are designed and shown to solve the issues of practical implementation on production engines. A basic pseudo-static engine-based calibration is generated for comparative purposes and the resulting static map is implemented in order to compare the fuel consumption and torque and air-fuel-ratio control with that of the proposed dynamic calibration method. Methods of optimal test signal design and parameter estimation for polynomial models are particularly detailed and studied in this thesis since polynomial models are frequently used in the process of dynamic calibration and control. Because of their ease of implementation, the input designs with different objective functions and optimization algorithms are discussed. Novel design criteria which lead to an improved parameter estimation and output prediction method are presented and verified using identified models of a 1.6L Zetec engine developed from test data obtained on the Liverpool University Powertrain Laboratory. Practical amplitude and rate constraints in engine experiments are considered in the optimization and optimal inputs are further validated to be effective in the black box modelling of the virtual engine. An additional experiment of input design for a MIMO model is presented based on a weighted optimization method. Besides the prediction error based estimation method, a simulation error based estimation method is proposed. This novel method is based on an unconstrained numerical optimization and any output fitness criterion can be used as the objective function. The effectiveness is also evaluated in a black box engine modelling and parameter estimations with a better output fitness of a simulation model are provided.

The freight transport has a fundamental role in the world’s economic development.Due to the flexibility of heavy-duty vehicles, a large part of freighttransport is carried out inland. Although the use of heavy-duty vehicles contributesto the economic growth, the increased fuel consumption and globalgreenhouse gas emission that come with it constantly challenge the transportationsector to adapt and develop more fuel-efficient methods to reduce suchside effects while fulfilling the transportation requirements.This thesis considers fuel-optimal highway driving for heavy-duty vehicles.A model predictive control algorithm for minimizing fuel consumptionwhile satisfying constraints on desired speed is developed and evaluated. Thecontroller uses the available topography information of the road ahead of thevehicle in order to achieve an efficient vehicle control while satisfying a certaintrip time requirement. Under the assumption of fixed gear during the drivemission, the actual nonlinear problem is re-formulated as a real-time optimalcontrol problem based on MPC theory with a quadratic cost function and linearconstraints at each receding horizon of the drive mission. The QP problem isthen solved online and the resulting first control action is applied to the vehiclefor forward movement.The feasibility to implement such an algorithm on a control unit with limitedcomputational power is investigated and shown to be possible. Both therequirement of low computational complexity and low memory occupation arefulfilled by the tailored quadratic programming algorithm developed in thisthesis. The algorithm is fast enough to provide a solution within each samplinginterval.The overall control algorithm is implemented on a G5 control unit andtested in real life with a Scania truck during highway driving test. The resultsfrom both the real implementation and extensive simulations indicate that themethod provides a fuel-efficient vehicle behavior and is competitive with a rulebasedcontroller.
Transport av gods har en grundläggande roll i världens ekonomiska utveckling.På grund av flexibiliteten hos tunga fordon, utförs en stor del av allgodstransport med hjälp av dem. Trots att användning av tunga fordon bidrartill ekonomisk tillväxt, utgör bränsleförbrukning tillsammans med den ökadeutsläpp av växthusgas en utmaning för transportföretag att anpassa och utvecklamer bränslesnål och miljövänligare transportteknologi för tunga fordon.I detta examensarbete fokuserar man på körningen av lastbil på motorvägar.En bränsle optimal förutsägande styralgoritm är utvecklad och utvärderad.Algoritmen utnyttjar framför allt topografi information om vägen framför fordonetså att den kan planera körningen på ett bränslesparande sätt samtidigtsom den uppfyller ett visst tidskrav. Med antagande om konstant växel underkörningen, formuleras ett optimal styrningsproblem baserat på ett MPC ramverkmed kvadratisk målfunktion och linjära bivillkor. Den slutliga kvadratiskoptimeringsproblemet för varje styrhorisont är löst med hjälp av en för ändamåletframtagen QP-algoritm.Möjligheten att implementera en sådan algoritm på en inbyggd styrenhetär undersökt och veriferad. Både krav på låg beräkningskomplexitet och lågminnes användning är uppfylls av den MPC-anpassade QP-lösare som utvecklatsi detta examensarbete.Den slutliga styralgoritmen testades i verkligheten med en Scania lastbilpå motorväg. Resultat från både provkörning och simulering visar att metodenger en bränsleeffektiv körstrategi, som kan spara bränsle jämfört med en regelbaseradprediktiv farthållaren.

Volvo Powertrain tillverkar motorer och drivlinor till AB Volvos samtliga dotterbolag förutom Volvo Aero. Vid anläggningen i Skövde tillverkas motorer och delar till motorer och växellådor och vid anläggningen finns alla tre nödvändiga produktionsområden; gjuteri, bearbetning och montering. När rådande lågkonjunktur slog till stod bearbetningen med väldigt höga lagernivåer vilka företaget snabbt tvingades sänka då det blev huvudfokus från koncernledningen att minska det bundna kapitalet. Utan egentlig analys sattes nya gränsnivåer för lagren inom samtliga avdelningar på bearbetning och målet med examensarbetet har varit att ta fram en metod för att dimensionera säkerhetslagret på optimal nivå med bibehållen hög leveranssäkerhet. Därigenom skulle företagets lagernivåer kunna styrkas med hjälp av en teoretisk grund.

Som utgångspunkt har en lagernivådimensionering med servicenivåkonceptet SERV2 och där alla artiklar tillåts ha differentierade servicenivåer använts. Utifrån Volvo Powertrains förutsättningar har ett optimeringsproblem formulerats. Det visar sig vid närmare studie av detta problem att det är ett ickelinjärt heltalsproblem, vilket försvårar lösningsgången avsevärt. För att komma runt dessa beräkningsmässiga problem approximerades ett av bivillkoren för att ta fram en lösningsheuristik. Dock upptäcktes efter ett antal försök att denna inte uppfyllde samtliga bivillkor alla gånger varför det beslutades att låta heuristikens lösning fungera som startlösning till en sökmetod vid letandet efter lokalt optimum.

I rapporten beskrivs ingående vilka parametrar som behöver mätas och hur för att alla avdelningar ska använda samma mätmetod vid framtagande av nödvändiga indata. Metoden har implementerats i Excel där användaren får mata in värden på dessa parametrar vilka sedan används i de nödvändiga beräkningarna. De data som sedan presenteras som resultat är vilka batchstorlekar som ska produceras, vilken säkerhetslagernivå som ska gälla, vid vilken nivå en ny beställning ska genomföras samt uppnådd leveranssäkerhet.

Utöver denna del presenteras även ett nytt sätt att sköta lagerstyrningen i de fall där det finns en flaskhals tidigt i produktionsflödet och som därmed bestämmer produktionstakten i resten av flödet. Eftersom detta skapar en sugstyrning genom flödet där mellanlager är onödiga blir produktionen mer känslig för störningar, vilket leder till att tidigare dolda problem inom produktionen kommer upp till ytan.

Resultaten av genomförda simuleringar visar att metoden innebär minskade lagernivåer samtidigt som önskad leveranssäkerhet upprätthålls. Genom att implementera metoden kommer bearbetningen vid Volvo Powertrain i Skövde att få en metod att stödja sina beslut på vilken optimerar lagernivåerna samtidigt som en hög leveranssäkerhet garanteras.

Volvo Powertrain produces engines and drivelines to AB Volvo's subsidiaries except to Volvo Aero. At the plant in Skövde engines and parts for engines and transmissions are manufactured and the facility includes all three essential areas of production; casting, machining and assembly. When the current recession hit Volvo Powertrain were working with very high inventory levels, which the company was quickly forced to cut since it became the main focus of the group management to reduce the capital tied up. Without conducting any proper analysis were new stock limit levels set in all sections of the company. The aim of this master thesis was to develop a methodology for setting of safety stocks at optimum levels while maintaining high delivery reliability. This would allow the company's inventory levels to be defined using a theoretical basis.

As a starting point, a stock-level design with the service concept SERV2 together with allowing all articles to have differentiated levels of service was used. On the basis of Volvo Powertrain's conditions an optimization problem have been formulated. It turns out that this problem is a nonlinear integer problem, which makes solution very difficult. To overcome these computational problems one of the constraints were approximated in purpose to develop a heuristics. However, it was detected after several attempts, that the heuristics did not satisfy all the constraints at all times so it was decided to use the heuristic solution to act as a starting solution to a search method to search for a local optimum.

The report describes in detail the parameters that need to be measured and how to ensure that all departments are using the same method in the preparation of the necessary input data. The method has been implemented in Excel where the user may enter values for these parameters which are then used in the necessary calculations. The results that are presented includes what batch-sizes that are to be produced, the safety stock level to be applied, which re-order point  to be used and achieved service level.

In addition the report also presents a new way to manage stock control in cases where there is a bottleneck early in the production flow which therefore determines the rate of production in the rest of the flow. Since this creates a pull system through the process flow, the stock between the production steps is unnecessary. A drawback is that the production becomes more sensitive to disturbances but means that previously hidden problems in the production reach the surface.

The results of the simulations attempted show that the method involves reduction of inventory levels at the same time as the desired service level is maintained. By implementing the method Volvo Powertrain in Skövde will have a method to support their decisions which optimizes inventory levels at the same time as high service levels are guaranteed.

Hybrid powertrains represent the current trend on passenger cars. The purpose of thisreport is to create a basic model of a hybrid powertrain in Matlab/Simulinkenvironment and study their performance over certification driving cycle. Threecommonly used architectures are modeled and discussed in Simulink. Hence, the basiccomponents of a powertrain – battery, electric machine and combustion engine – arestudied and basic models are realized. A Thevenin equivalent circuit is used to simulatethe behavior of the battery, and the combustion engine is modeled after a Willansmodel. The electric machine model is based on a known efficiency map. Then, thearchitectures are created as well as their control strategies. The control strategies arecreated through state diagrams, and implemented into the Simulink model viaStateflow charts. A validation procedure is presented in order to study the consistencyof the models.
Hybrid drivlinor representerar en central personbilstrend. Syftet med rapporten är attpresentera en grundläggande modell för en hybrid drivlina i Matlab/Simulink. Trearkitekturer behandlas och har implementerats i Simulink. Sedan studeras degrundläggande komponenterna i ett drivaggregat (batteri, elmaskin ochförbränningsmotor). En Thevenin-ekvivalent krets används för att simulera batterietsbeteende. Förbränningsmotorn är modellerad efter en Willans-modell.Elmaskinmodellen är baserad på en känd verkningsgradsmapp. De tillhörandestyrstrategierna med hjälp av tillståndsdiagram. De implementeras i Simulinkmodellenmed hjälp av Stateflow-diagram. Ett valideringsförfarande presenteras ochvisar modellernas konsistens.

The rise in overall powertrain complexity and the stringent performance requirements of a hybrid electric vehicle (HEV) have elevated the role of its powertrain control strategy to considerable importance. Iterative modeling and simulation form an integral part of the control strategy design process and industry engineers rely on proprietary ?legacy? models to rapidly develop and implement control strategies. However, others must initiate new algorithms and models in order to develop production-capable control systems. This thesis demonstrates the development and validation of a charge-sustaining control algorithm for a through-the-road (TTR) parallel hybrid (diesel-electric) powertrain. Some unique approaches used in powertrain-level control of other commercial and prototype vehicles have been adopted to incrementally develop this control strategy. The real-time performance of the control strategy has been analyzed through on-road and chassis dynamometer tests over several standard drive cycles. Substantial quantitative improvements in the overall HEV performance over the stock configuration, including better acceleration and fuel-economy have been achieved.

Search and rescue operations in the Alpine area must be carried out as soon as possible to safeguard the lives of those involved in an accident. The use of drones in this area is of great interest due to the effectiveness with which it is possible to carry out SER operations in a short time. The AirBorne project deals with the development and study of drones to be applied in this field, in collaboration with the Aslatech company. This thesis aims to analyze the construction techniques of these drones and analyze the differences between two configurations to select the best components to be included in a final configuration. It also analyzes a key point for drones used in SER operations, ie control. An obstacle avoidance algorithm is presented and analyzed based on the use of artificial potentials. A simulation environment is then presented and analyzed in which a drone with ultrasound sensors will be simulated. A version of the obstacle avoidance control will be adapted to the specific case of ultrasonic sensors, analyzing the differences and testing their performance and feasibility

The new emission regulations for new trucks was made to decrease the CO2 emissions by 30% from 2020 to 2030. One of the solutions is hybridizing the truck powertrain with 48V or 600V that can recover brake energy with electrical machines and batteries. The control of this hybrid powertrain is key to increase fuel efficiency. The idea behind this approach is to combine two different power sources, an internal combustion engine and a battery driven electric machine, and use both to provide tractive forces to the vehicle. This approach requires a HEV controller to operate the power flow within the systems. The HEV controller is the key to maximize fuel savings which contains an energy management strategy. It uses the knowledge of the road profile ahead by GPS and maps, and strongly interacts with the control of the cruise speed, automated gear shifts, powertrain modes and state of charge. In this master thesis, the dynamic programming strategy is used as predictive energy management for hybrid electric truck in forward- facing simulation environment. An analysis of predictive energy management is thus done for receding and full horizon length on flat and hilly drive cycle, where fuel consumption and recuperation energy will be regarded as the primary factor. Another important factor to consider is the powertrain mode of the vehicle with different penalty values. The result from horizon study indicates that the long receding horizon length has a benefit to store more recuperative energy. The fuel consumption is decreased for all drive cycle in the comparison with existing Volvo’s strategy.

To cope with the increasing demand of a more sustainable mobility, the main Original Equipment Manufacturers are producing vehicles equipped with hybrid propulsion systems that increase the overall vehicle efficiency and mitigate the emission problem at a local level. The newly gained degrees of freedom of the hybrid powertrain need to be handled by advanced energy management techniques that allow to fully exploit the system capabilities. In this thesis we propose an optimal control approach to the solution of the energy management problem, putting emphasis on the importance of accurate models for the reliability of the optimization solution. In the first part of the thesis we address the energy management problem for a hybrid electric vehicle, including the mitigation of the battery aging mechanisms. We show that, with an optimal management strategy, we could extend the battery life up to 25% for some driving cycles while keeping the fuel savings performance substantially unaltered. In the second part of the thesis we focus on the hydrostatic hybrid transmission, a different hybridization solution that is able to fulfill the high power demand of heavy duty off-highway vehicles. Also in this case, we formulate the energy management problem as an optimal control problem, dealing with the complexity introduced by the discrete valve actuations in the framework of mixed-integer optimal control. We show that, using hydraulic accumulators to recover energy from the regenerative braking, we could reduce fuel consumption up to 13% for a typical driving cycle. In the third and last part of the thesis we show how the optimization approach can be used to systematically design and calibrate control algorithms, casting the calibration problem into a Linear Matrix Inequality. We first develop a non-overshooting closed-loop control for the actuation pressure of a wet clutch, proving the effectiveness of the control on an experimental setup. Finally, we focus on the design of a dead-zone based kinematic observer for the estimation of the lateral velocity of a road vehicle. The structure of the observer presents good noise rejection performance, allowing for the selection of a higher observer gain that improves the estimation accuracy.

In diesel-electric powertrains, the wheels are mechanically decoupled from the internal combustion engine (ICE). The conventional control approach for such a powertrain is to let the driver control the traction motor while the ICE realizes speed control, causing power to be pulled through the powertrain. An alternative approach is to push power forward by letting the driver control the ICE instead. In this thesis, a conceptual simulation model of a diesel-electric powertrain is compiled and the charcteristics of this novel approach investigated. It is concluded that the new approach makes full ICE power utilization possible even with engine performance reductions present, and also that it handles load prioritization in a natural way. However, takeoff from standstill and low-speed driving become difficult due to the effective gear ratio growing towards infinity for decreasing vehicle speed, causing high traction torques at low speed.

With the introduction of electronic control units to automotive vehicles, system complexity has increased. With this change in complexity, new standards have been created to ensure safety at the system level for these vehicles. Furthermore, vehicles have become increasingly complex with the push for electrification of automotive vehicles, which has resulted in the creation of hybrid electric and battery electric vehicles. The goal of this thesis is to provide an example of a hazard and operability analysis as well as a hazard and risk analysis for a hybrid electric vehicle. Additionally, the safety standards developed do not align well with educational prototype vehicles because the standards are designed for corporations. The hybrid vehicle supervisory controller example within this thesis demonstrates how to define a system and then perform system-level analytical techniques to identify potential failures and associated requirements. Ultimately, through this analysis suggestions are made on how best to reduce system complexity and improve system safety of a student built prototype vehicle.
Master of Science

This thesis discusses a general approach to hybrid powertrain control based on optimisation and optimal control techniques. A typical strategy comprises a high level non-linear control for optimised energy efficiency, and a lower level Linear Quadratic Regulator (LQR) to track the high-level demand signals and minimise the first torsional vibration mode. The approach is demonstrated in simulation using a model of the Toyota Prius hybrid vehicle, and comparisons are made with a simpler control system which uses proportional integral (PI) control at the lower level. The powertrain of the Toyota Prius has a parallel configuration, comprising a motor, engine and generator connected via an epicyclic gear train. High level control is determined by a Power Efficient Controller (PE C) which dynamically varies the operating demands for the motor, engine and generator. The PEC is an integrated nonlinear controller based on an iterative downhill search strategy for optimising energy efficiency and battery state of charge criteria, and fully accounts for the non-linear nature of the various efficiency maps. The PEC demand signals are passed onto the LQR controller where a cost function balances the importance of deviations from these demands against an additional criterion relating to the amplitude of driveline vibrations. System non-linearity is again accounted for at the lower level through gain scheduling of the LQR controller. Controller performance is assessed. in simulation, the results being compared with a reference system that uses simple PI action to deliver low-level control. Consideration is also given to assessing performance against that of a more general, fully non-linear dynamic optimal controller.

This thesis demonstrates a practical implementation of a sensorless permanent magnet synchronousmotor (PMSM) drive for vehicle propulsion. The main design parameters and overall properties of themotor drive are derived for the case of an on-board electric powertrain as a substitute to the lift shuttle indownhill (DH) mountain biking.The theory behind field oriented control (FOC) for sensorless PMSMs is analyzed in some detail.Controller-inverter hardware and software are designed and prototyped in accordance with the deriveddesign parameters. Initial tuning and testing in a test bench environment is described. The powertrain isfinally installed on a test bike and tested on an incline. It is found that the performance of the controllerinvertercomplies with the target design parameters.