An emerging technology is the hybridization of wheel loaders. Since wheel loaders commonly operate in repetitive cycles it should be possible to use this information to develop an efficient energy management strategy that decreases fuel consumption. The purpose of this thesis is to evaluate if and how this can be done in a real-time online application. The strategy that is developed is based on pattern recognition and Equivalent Consumption Minimization Strategy (ECMS), which together is called Adaptive ECMS (A-ECMS). Pattern recognition uses information about the repetitive cycles and predicts the operating cycle, which can be done with Neural Network or Rule-Based methods. The prediction is then used in ECMS to compute the optimal power distribution of fuel and battery power. For a robust system it is important with stability implementations in ECMS to protect the machine, which can be done by adjusting the cost function that is minimized. The result from these implementations in a quasistatic simulation environment is an improvement in fuel consumption by 7.59 % compared to not utilizing the battery at all.

La propulsion des véhicules électriques hybrides parallèles est généralement assurée par un moteur à combustion interne combiné à une machine électrique réversible. Les flux de puissance entre ces deux organes de traction sont déterminés par un algorithme de supervision, qui vise à réduire la consommation de carburant et éventuellement les émissions de certains polluants. Dans la littérature, la théorie de la commande optimale est maintenant reconnue comme étant un cadre puissant pour l'élaboration de lois de commande pour la gestion énergétique des véhicules full-hybrides. Ces stratégies, dénommée " Stratégies de Minimisation de la Consommation Equivalente " (ECMS) sont basée sur le principe du Maximum de Pontryagin. Pour démontrer l'optimalité de l'ECMS, on doit supposer que les limites du système de stockage ne sont pas atteintes durant le cycle de conduite. Il n'est plus possible de faire cette hypothèse lorsque l'on considère les véhicules micro et mild hybrides étudiés dans cette thèse car la variable d'état atteint généralement plusieurs fois les bornes. Des outils mathématiques adaptés à l'étude des problèmes de commande avec contraintes sur l'état sont présentés et appliqués à deux problèmes en lien avec la gestion énergétique. Le premier problème consiste à déterminer le profil optimal de la tension aux bornes d'un pack d'ultra-capacités. Le second problème se concentre sur un système électrique intégrant deux stockeurs. L'accent est mis sur l'étude des conditions d'optimalités valables lorsque les contraintes sur l'état sont actives. Les conséquences de ces conditions pour la commande en ligne sont mises en avant et exploitées afin de concevoir une commande en temps réel. Les performances sont évaluées à l'aide d'un prototype. Une comparaison avec une approche de type ECMS plus classique est également présentée.

This thesis (1) reports the development of simulation tools and control strategies for optimizing hybrid electric vehicle (HEV) energy management, and (2) reports the design and testing of a hydraulic hybrid school bus (HHB) prototype. A hybrid vehicle is one that combines two or more energy sources for use in vehicle propulsion. Hybrid electric vehicles have become popular in the consumer market due to their greatly improved fuel economy over conventional vehicles. The control strategy of an HEV has a paramount effect on its fuel economy performance. In this thesis, backward-looking and forward-looking simulations of three HEV architectures (parallel, power-split and 2-mode power-split) are developed. The Equivalent Cost Minimization Strategy (ECMS), which weights electrical power as an equivalent fuel usage, is then studied in great detail and improvements are suggested. Specifically, the robustness of an ECMS controller is improved by linking the equivalence factor to dynamic programming and then further tailoring its functional form. High-fidelity vehicle simulations over multiple drive-cycles are performed to measure the improved performance of the new ECMS controller, and to show its potential for online application. While HEVs are prominent in the consumer market and studied extensively in current literature, hydraulic hybrid vehicles (HHVs) only exist as heavy utility vehicle prototypes. The second half of this thesis reports design, construction, and testing of a hydraulic hybrid school bus prototype. Design considerations, simulation results, and preliminary testing results are reported, which indicate the strong potential for hydraulic hybrids to improve fuel economy in the school bus vehicle segment.

La gestion d'énergie d'un véhicule hybride consiste à développer une stratégie, qui détermine à chaque instant la répartition des flux d'énergie thermique et électrique, minimisant la consommation globale du véhicule. La modélisation de la consommation du véhicule hybride permet d'écrire cette problématique sous la forme d'un problème d'optimisation dynamique sous contraintes d'évolutions. Ce problème est résolu de façon optimale lorsque l'ensemble des conditions de roulage sont connues à priori. La commande optimale obtenue sert de référence pour évaluer la performance des stratégies embarquées dans le véhicule. En s'appuyant sur la théorie de l'optimisation optimale, deux stratégies ont été crées : l'une prédictive qui a été testée sur un simulateur numérique et une autre, reposant sur le principe du problème dual, qui a été embarqué avec succès sur deux véhicules hybrides conventionnels. Pour les hybrides rechargeables, leur capacité énergétique et la possibilité de se recharger sur le réseau électrique libère des contraintes dans la problématique d'optimisation énergétique. C'est pourquoi, une nouvelle stratégie spécifique a été développée dans l'objectif de profiter au maximum de l'énergie électrique embarquée pour minimiser les émissions du véhicule. Pour l'ensemble des véhicules hybrides, la batterie est un composant clef dont le vieillissement vient modifier sa rentabilité économique et énergétique. C'est pourquoi un observateur a été conçu pour fournir une information précise de la température interne des cellules. Cette information est utilisée par une stratégie spécifique optimisant la consommation tout en préservant la batterie des températures extrêmes, nuisibles à sa longévité.

<p>The introduction of hybrid powertrains has made it possible to utilise unconventional engines as primary power units in vehicles. The free-piston energy converter (FPEC) is such an engine. It is a combination of a free-piston combustion engine and a linear electrical machine. The main features of this configuration are high efficiency and a rapid transient response.</p><p>In this thesis the free-piston energy converter as part of a hybrid powertrain is studied. One issue of the FPEC is the generation of pulsating power due to the reciprocating motion of the translator. These pulsations affect the components in the powertrain. However, it is shown that these pulsations can be handled by a normal sized DC-link capacitor bank. In addition, two approaches to reduce these pulsations are suggested: the first approach is using generator force control and the second approach is based on phase-shifted operation of two FPEC units. The latter approach results in higher frequency and lower amplitude of the pulsations, which reduce the capacitor losses.</p><p>The FPEC start-up requirements are analysed and by choosing the correct amplitude of the generator force during start-up the energy consumption can be minimised.</p><p>The performance gain of utilising the FPEC in a medium sized series hybrid electric vehicle (SHEV) is also studied. An FPEC model suitable for vehicle simulation is developed and a series hybrid powertrain, with the same performance as the Toyota Prius, is dimensioned and modelled.</p><p>Optimisation is utilised to find a lower limit on the SHEV's fuel consumption for a given drivecycle. In addition, three power management control strategies for the FPEC system are investigated: two load-following strategies using one and two FPEC units respectively and one strategy based on the ideas of an equivalent consumption minimisation (ECM) proposed earlier in the literature.</p><p>The results show a significant decrease in fuel consumption, compared to a diesel-generator powered SHEV, just by replacing the diesel-generator with an FPEC. This result is improved even more by using two FPEC units to generate the propulsion power, as this increases the efficiency at low loads. The ECM control strategy does not reduce the fuel consumption compared to the load-following strategies but gives a better utilisation of the available power sources.</p>

Durch die Integration mindestens eines weiteren Energiewandlers in den Antriebsstrang gewinnen parallele Hybridfahrzeuge einen zusätzlichen Freiheitsgrad gegenüber konventionellen Fahrzeugen. Neben der Auslegung und Effizienz der einzelnen Antriebskomponenten, ist vor allem die Nutzung dieses zusätzlichen Freiheitsgrades entscheidend dafür verantwortlich, inwiefern die beim Betrieb eines Hybridfahrzeugs erwünschten Ziele, wie die Minimierung des Kraftstoffverbrauchs oder der Abgasemissionen, erreicht werden können. Zuständig dafür sind sogenannte Betriebsstrategien. In einem ersten Schritt gibt die vorliegende Diplomarbeit einen Überblick aktueller Betriebsstrategieansätze für Fahrzeuge mit einer parallelen Hybridarchitektur und stellt ausgewählte Beiträge wertend gegenüber. Anschließend wird mit der optimierungsbasierten Equivalent Consumption Minimization Strategy (ECMS) ein vielversprechender Ansatz in ein MATLAB/Simulink-Längsdynamikmodell umgesetzt. Die für diesen Ansatz maßgebliche Bestimmung des Äquivalenzfaktors erfolgt dabei ohne Verwendung von Prädiktionsdaten. Eine Gegenüberstellung der erzielten Kraftstoffverbrauchswerte zu denen einer regelbasierten Betriebsstrategie, zeigt die Vorteile des implementierten ECMS-Ansatzes. Um den unterschiedlichen Ladezuständen am Fahrtende gerecht zu werden, wird eine ladungsabhängige Kraftstoffkorrektur vorgestellt. / By integrating at least one additional energy converter into the drive train, parallel hybrid vehicles gain an additional degree of freedom compared to conventional vehicles. In addition to the design and efficiency of the individual drive train components, especially the use of this additional degree of freedom is the key responsible to achieve the desired goals in the operation of a hybrid vehicle, such as minimizing fuel consumption and exhaust emissions. Responsible for this are so-called supervisory strategies. In a first step, the present thesis provides an overview of current supervisory control strategies for vehicles with a parallel hybrid architecture and compares selected approaches. In a second step, a promising Equivalent Consumption Minimization Strategy (ECMS) is chosen and implemented in a MATLAB/Simulink-longitudinal dynamics model. This approach relates on the determination of the equivalence factor which is carried out without the use of prediction data. A comparison of the fuel consumption, obtained for a rule-based supervisory strategy, shows the advantages of the implemented ECMS approach. To consider the different states of charge at the end of the trip, a charge-dependent fuel correction will be presented.

In recent years, rules and regulations regarding fuel consumption of vehicles and the amount of emissions produced by them are becoming stricter. This has led the automotive industry to develop more advanced solutions to propel vehicles to meet the legal requirements. The Hybrid Electric Vehicle is one of the solutions that is becoming more popular in the automotive industry. It consists of an electrical driveline combined with a conventional powertrain, propelled by either a diesel or petrol engine. Two power sources create the possibility to choose when and how to use the power sources to propel the vehicle. The strategy that decides how this is done is referred to as an energy management strategy. Today most energy management strategies only try to reduce fuel consumption using models that describe the steady state behaviour of the engine. In other words, no reduction of emissions is achieved and all transient behaviour is considered negligible.  In this thesis, an energy management strategy incorporating engine dynamics to reduce fuel consumption and nitrogen oxide emissions have been designed. First, the models that describe how fuel consumption and nitrogen oxide emissions behave during transient engine operation are developed. Then, an energy management strategy is developed consisting of a model predictive controller that combines the equivalent consumption minimization strategy and convex optimization. Results indicate that by considering engine dynamics in the energy management strategy, both fuel consumption and nitrogen oxide emissions can be reduced. Furthermore, it is also shown that the major reduction in fuel consumption and nitrogen oxide emissions is achieved for short prediction horizons.

The requirements on fuel consumption and emissions for passenger cars are getting stricter every year. This has forced the vehicle industry to look for ways to improve the performance of the driveline. With the increasing focus on electrification, a common method is to combine an electrical driveline with a conventional driveline that uses a petrol or diesel engine, thus creating a hybrid electric vehicle. To fully be able to utilise the potential of the driveline in such a vehicle, an efficient energy management strategy is needed. This thesis describes the development of an efficient route-based energy management strategy. Three different optimisation strategies are combined, deterministic dynamic programming, equivalent consumption minimisation strategy and convex optimisation, together with segmentation of the input data. The developed strategy shows a decrease in computational time with up to more than one hundred times compared to a benchmark algorithm. When implemented in Volvo's simulation tool, VSim, substantial fuel savings of up to ten percent is shown compared to a charge-depleting charge-sustain strategy.

More restrictive emission legislations, rising fuel prices and the realisation that oil is a limited resource have lead to the emergence of the hybrid electric vehicles.To fully utilise the potential of the hybrid electric vehicles, energy management strategies are needed. The main objective of the strategy is to ensure that the limited electric energy is utilised in an efficient manner.This thesis develops and evaluates an optimisation based energy management strategy for plug-in hybrid electric vehicles. The optimisation methods used are based on a dynamic programming and ECMS approach. The strategy is validated against Vsim, Volvo Cars' performance and fuel consumption analysis tool as well as against strategies where parts of the optimisation is replaced by logic. The results show that the developed strategy consumes less fuel both compared to the corresponding Vsim strategy and the logic strategies.

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