This research systematically compares various electrified vehicles based upon electrification levels and powertrain configurations. A series of novel hybrid electric powertrain systems based on the newly proposed Hybridized Automated Manual Transmission (HAMT) concept are introduced. One representative hybrid powertrain system is selected to illustrate their operation principle. The new HAMT-based hybrid powertrain system overcomes the bottleneck problem of mainstream power-split hybrid systems with relatively low torque capacity and the constraint for utility vehicle electrification, and presents advantages over other hybrid powertrain systems in efficiency and costs. In addition, the new hybrid powertrain system can deliver continuous output torque by filling torque hole during gearshift, through coordinated control of engine, motor, and transmission, improving the driveability of regular Automated Manual Transmission (AMT), whose applications have been hampered by torque hole over the past years. The proposed HAMT-based hybrid systems with improved torque capacity, efficiency, costs, and driveability come with a compact design and more flexible operation through the amount of gearwheels equivalent to a 5-speed AMT to achieve 8 variable gear ratios for the Hybrid Electric Vehicle (HEV) mode and Electric Vehicle (EV) mode operations of a Plug-in Hybrid Electric Vehicle (PHEV). Model-based optimization, dynamics analysis, and powertrain control strategies have been introduced for a PHEV with a representative 8-speed HAMT. Vehicle simulations have been made to study and verify the capability and advantages of the new electrified powertrain system. Firstly, the operation principles of various HAMTs are discussed through detailed power flows at each gear. The fundamental principles of typical HAMT variations are explained using a new power-flow triangle with three ports. Based on the concept of Torque Gap Filler (TGF), a set of HAMT system designs have been introduced and closely studied to provide continuous and stable output torque. The selected hybrid powertrain system equipped with a representative HAMT system supports both HEV mode and EV mode with eight variable gear ratios for each mode. Among the eight forward gear ratios, six are independent and two are dependent on the other gears. Combinations of dog clutches at all gears are designed to eliminate torque holes. Gear ratios and gearshift schedule of the 8-speed HAMT are designed to support the new design. Torque paths at each gear are illustrated and transient scenarios including gearshifts and mode transitions are investigated. The gear ratio of each gear is determined by considering the unique clutch combination of this HAMT, using the classical gear ratio design method - Progressive Ratio Steps. Due to the broader high efficiency operation region of electric motors, a model-based optimization method is used to determine the two gear ratios for the EV mode to achieve better fuel economy and avoid unnecessary gearshifts. Dynamic Programming (DP) is used to identify the optimal gear ratios, considering vehicle fuel economy for the EPA75 and Highway Fuel Economy Fuel Test (HWFET) driving cycles. The 4th and 6th gears among the eight gear ratios in the EV mode of PHEV are based on 2-speed gearbox design for an EV, and their gearshift schedules are determined by optimization. Combining the considerations for the hybrid and EV modes of a PHEV, key elements of the proposed HAMT system, including gearshift schedule, clutch combination, and gear ratios for highly efficient operation are determined. The more challenging driveability issues during mode transition from EV to HEV and power-on gearshift with TGF during acceleration are addressed. Both of these two operations require relatively high power/torque outputs and involve multiple powertrain components, including engine, motor, main clutch and gearbox, within a period of two seconds. A lumped-mass model (LMM) of the HAMT-based hybrid vehicle is built to analyze the driveline dynamics in two steady states and four transient states. Each of these states is analyzed independently, according to states of main clutch and gear selectors, considering different phases of the TGF operation and EV-HEV mode transition. The methods for modeling the discontinuity of clutch torque and dog clutch inside the HAMT are discussed to support the subsequent powertrain system modeling and control development. To identify the optimal control schemes for model transition and gearshift, the model-based optimization method for a post-transmission parallel PHEV is developed. The vehicle powertrain model was initially built using AUTONOMIE and MATLAB/Simulink with primary parameters from a prototype PHEV and its dSPACE ASM model developed at University of Victoria. System dynamics in EV mode and hybrid mode are described as a group of state-space equations, which are further discretized into matrix form to simplify the optimization search. A DP-based global optimization method is used to identify the optimal control inputs, including engine torque, motor torque, and main clutch torque. Four principles for desirable EV-HEV mode transitions are extracted based on the results of the optimization. To model different operation modes and complex power flows, the initial baseline powertrain system model is then replaced by a customized MATLAB/SimDriveline model. In this new physics-based powertrain model, gearshift actuators and controller are added to model the gearshift and mode transition processes. To achieve good driveability, the TGF feature of the HAMT design is split into five transient and two steady phases, each corresponding to a fundamental operating mode. Control logics of upshift and downshift, as well as EV-HEV mode transition are introduced. Four principles of mode transition derived from global optimization results are introduced for powertrain system control. Simulations of the HAMT-based hybrid powertrain operations have been carried out to verify the functionality and advantages of the proposed HAMT design in achieving excellent driveability during mode transition and gearshifts. Through controlled coordination of engine, motor and main clutch, EV-HEV mode transition can be achieved smoothly within a period of 2-3 seconds. Even slight driveline fluctuation can be eliminated by dedicated anti-shuffle control with the motors as actuators. The same simulation model also demonstrates excellent driveability during power-on gearshift. Comparing simulation results with and without TGF shows that this new hybrid powertrain system can effectively eliminate torque holes during gearshift. With the demonstrated advantages of this new system in efficiency, torque capacity, simplicity in design and manufacturing costs over its existing rivals, the research provides a promising alternative to mainstream power-split hybrid electric powertrain system design. / Graduate

This thesis explores the possibility of using an optimal control scheme called Model Predictive Control (MPC), to control climatization systems for electric vehicles. Some components of electric vehicles, for example the batteries and power electronics, are sensitive to temperature and for this reason it is important that their temperature is well regulated. Furthermore, like all vehicles, the cab also needs to be heated and cooled. One of the weaknesses of electric vehicles is their range, for this reason it is important that the temperature control is energy efficient. Once the range of electric vehicles is increased the down sides compared to traditional combustion engine vehicles decrease, which could lead to an increase in the usage of electric vehicles. This could in turn lead to a decrease of greenhouse gas emission in the transportation sector. With the help of MPC it is possible for the controller to take more factors into consideration when controlling the system than just temperature and in this thesis the power consumption and noise are also taken into consideration. A simple model where parts of the climate system’s circuits were seen as point masses was developed, with nonlinear heat transfers occurring between them, which in turn were controlled by actuators such as fans, pumps and valves. The model was created using Simulink and MATLAB, and the MPC toolbox was used to develop nonlinear MPC controllers to control the climate system. A standard nonlinear MPC, a nonlinear MPC with custom cost functions and a PI controller where all developed and compared in simulations of a cooling scenario. The controllers were designed to control the temperatures of the battery, power electronics and the cab of an electric vehicle. The results of the thesis indicate that MPC could reduce power consumption for the climate control system, it was however not possible to draw any final conclusions as the PI controller that the MPC controllers were compared to was not well optimized for the system. The MPC controllers could benefit from further work, most importantly by applying a more sophisticated tuning method to the controller weights. What was certain was that it is possible to apply this type of centralized controller to very complex systems and achieve robustness without external logic. Even with the controller keeping track of six different temperatures and controlling 15 actuators, the control loop runs much faster than real time on a modern computer which shows promise with regard to implementing it on an embedded system.