This thesis develops dynamic models for the two-mode FWD EVT, develops a control system based on those models that is capable of meeting driver torque demands and performing synchronous mode shifts between different EVT modes while also accommodating preferred engine operating points. The two-input two-output transmission controller proposed herein incorporates motor-generator dynamics, is based on a general state-space integral control structure, and has feedback gains determined using linear quadratic regulator (LQR) optimization. Dynamic modeling of the vehicle is categorized as dynamic modeling of the mechanical and electrical subsystems where the mechanical subsystem consists of the planetary gear sets, the transmission and the engine whereas the electrical subsystem consists of the motor-generator units and the battery pack. A discussion of load torque is also considered as part of the mechanical subsystem. With the help of these derived dynamic models, a distinction is made between dynamic output torque and steady-state output torque. The overall control system consisting of multiple subsystems such as the human driver, power management unit (PMU), friction brakes, combustion engine, transmission control unit (TCU) and motor-generator units is designed. The logic for synchronous mode shifts between different EVT modes is also detailed as part of the control system design. Finally, the thesis presents results for responses in individual operating modes, EVT mode shifting and a full UDDS drive cycle simulation.

The well-to-wheel (WTW) environmental performance of plug-in hybrid electric vehicles (PHEVs) is sensitive to driving patterns, which vary within and across regions. This thesis develops and applies a novel approach for estimating specific regional driving patterns. The approach employs a macroscopic traffic assignment model linked with a vehicle motion model to construct driving cycles, which is done for a wide range of driving patterns. For each driving cycle, the tank-to-wheel energy use of two PHEVs and comparable non-plug-in alternatives is estimated. These estimates are then employed within a WTW analysis to investigate implications of driving patterns on the energy use and greenhouse gas emission of PHEVs, and the WTW performance of PHEVs relative to non-plug-in alternatives for various electricity generation scenarios. The results of the WTW analysis demonstrate that driving patterns and the electricity generation supply interact to substantially impact the WTW performance of PHEVs.

The well-to-wheel (WTW) environmental performance of plug-in hybrid electric vehicles (PHEVs) is sensitive to driving patterns, which vary within and across regions. This thesis develops and applies a novel approach for estimating specific regional driving patterns. The approach employs a macroscopic traffic assignment model linked with a vehicle motion model to construct driving cycles, which is done for a wide range of driving patterns. For each driving cycle, the tank-to-wheel energy use of two PHEVs and comparable non-plug-in alternatives is estimated. These estimates are then employed within a WTW analysis to investigate implications of driving patterns on the energy use and greenhouse gas emission of PHEVs, and the WTW performance of PHEVs relative to non-plug-in alternatives for various electricity generation scenarios. The results of the WTW analysis demonstrate that driving patterns and the electricity generation supply interact to substantially impact the WTW performance of PHEVs.

Les principaux objectifs de cette étude est de fournir les informations essentielles sur le comportement thermique des cellules de batterie pour une application automobile, en particulier pour les véhicules électriques et hybrides. Cette application est notre cadre de travail expérimental afin de développer un modèle électro-thermique 3D efficace pour les cellules lithium-ion et du pack batterie. L'étude expérimentale se concentre sur la distribution de température en différents points de la surface de la cellule, de l'impact de différents débits constants, et également l'importance du système de refroidissement sur le comportement en température de la batterie. Cette thèse met en évidence le comportement de température de la cellule dans des conditions de décharge agressive et de l'impact de l'empilement de plusieurs cellules à l'intérieur de la batterie. Une étude de cas sur le comportement thermique de la cellule dans une application véhicule électrique hybride série est proposée pour compléter les cycles de conduite en utilisant différentes stratégies de refroidissement. En outre, l'étude expérimentale est étendue à la caractéristique du comportement de refroidissement par flux d'air à l'intérieur de la batterie, en utilisant le système d'image de particules (PIV). Le modèle électro-thermique CFD 3D est développé sous un logiciel Open Source OpenFOAM. L'objectif principal est d'obtenir un modèle relativement simple mais précis avec un temps de calcul raisonnable. Le modèle proposé, estime la production de chaleur, à partir du courant de la batterie et la résistance interne en fonction de la température, le transfert de chaleur par conduction, convection forcée et rayonnement. / The main objectives of this study are to provide the essential information on the thermal behaviour of the battery cells for automotive purpose especially for EVs and HEVs through experimental work in order to develop an effective 3D electro-thermal model for lithium ion battery cells and pack. The experimental study is focusing on the distribution of temperature at various points of the battery cell surface, impact of different constant discharge rates, and also the importance of cooling system on the battery temperature behaviour. This thesis highlights the battery cell temperature under abuse discharge condition and the impact of stacking the battery cells inside the battery pack. Impact of different temperature and SOC on the battery cell internal resistance and a case study on the battery cell thermal behaviour used in a series HEV to complete driving cycles using different cooling strategies are also studied. Furthermore, the experimental study is extended to the characteristic of the cooling air flow behaviour inside the battery pack, using particulate image velocimetry (PIV) system. The 3D electro-thermal CFD model is implemented in a free, open source CFD software package called OpenFOAM. The target is to have a relatively simple but accurate model with reasonable computation time. This proposed model considers the heat generation from battery current and internal resistance as a function of temperature, heat transfer through conduction, forced convection and radiation.

The work deals with relatively new components allowing electric energy accumulation – ultracapacitors. It focuses on their application in traffic systems – in independent electric vehicles. Design and verification of a system with ultracapacitor and DC/DC adaptive converter was done. Control of the adaptive converter modifies very positively the time wafeform of the traction accumulator current during the drive cycle. The designed connection of ultracapacitor and DC/DC converter implemented in the drive structure of experimental electric vehicle with induction machine contributes to increment the action radius of the vehicle by 16% (determined by experimental verification). This result was achived particularly by limitation of traction accumulator current peaks, And by more effective storage of energy gained by recuperative braking of the vehicle as well. The core of the system is a control of the adaptive converter in order to provide an active filtration of the accumulator’s current to its long-period mean value, i.e. elimination of current (power) peaks. These are caused by acceleration from non-zero initial vehicle speed or by recuperative braking. This is done by a subsidiary current loop. The converter has a superior voltage regulation loop, which sets in long-time period the voltage of ultracapacitors to the proper value – indirectly dependent on the speed of the vehicle. This ensures the appropriate energy management of the ultracapacitor. In the following, properties of test set of ultracapacitors were verified. Finally, methods of suppression of capacity variability influence in series connection of these components were compiled and critically reviewed.

Indiana University-Purdue University Indianapolis (IUPUI) / There is a strong urge for advanced diagnosis method, especially in high power battery packs and high energy density cell design applications, such as electric vehicle (EV) and hybrid electric vehicle segment, due to safety concerns. Accurate and robust diagnosis methods are required in order to optimize battery charge utilization and improve EV range. Battery faults cause significant model parameter variation affecting battery internal states and output. This work is focused on developing diagnosis method to reliably detect various faults inside lithium-ion cell using electrochemical model based observer and fuzzy logic algorithm, which is implementable in real-time. The internal states and outputs from battery plant model were compared against those from the electrochemical model based observer to generate the residuals. These residuals and states were further used in a fuzzy logic based residual evaluation algorithm in order to detect the battery faults. Simulation results show that the proposed methodology is able to detect various fault types including overcharge, over-discharge and aged battery quickly and reliably, thus providing an effective and accurate way of diagnosing li-ion battery faults.

Premature loss of capacity, mode of partial charge, additives, negative electrode, lead acid battery, lead-acid battery cycling, hybrid electric vehicle, traction battery, ebonex, titanium dioxide