STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE

This report presents the research results of battery modeling and control for hybrid electric vehicles (HEV). The simulation study is conducted using plug-and-play powertrain and vehicle development software, Autonomie. The base vehicle model used for testing the performance of battery model and battery control strategy is the Prius MY04, a power-split hybrid electric vehicle model in Autonomie. To evaluate the battery performance for HEV applications, the Prius MY04 model and its powertrain energy flow in various vehicle operating modes are analyzed. The power outputs of the major powertrain components under different driving cycles are discussed with a focus on battery performance. The simulation results show that the vehicle fuel economy calculated by the Autonomie Prius MY04 model does not match very well with the official data provided by the department of energy (DOE). It is also found that the original battery model does not consider the impact of environmental temperature on battery cell capacities. To improve battery model, this study includes battery current loss on coulomb coefficient and the impact of environmental temperature on battery cell capacity in the model. In addition, voltage losses on both double layer effect and diffusion effect are included in the new battery model. The simulation results with new battery model show the reduced fuel economy error to the DOE data comparing with the original Autonomie Prius MY04 model.

Predictive control of hybrid vehicle powertrain for intelligent energy management

This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.

THERMAL CHARACTERIZATION OF COMBUSTION CHAMBER COMPONENTS IN A GASOLINE TURBOCHARGED DIRECT INJECTION (GTDI) ENGINE

This report is a PhD dissertation proposal to study the in-cylinder temperature and heat flux distributions within a gasoline turbocharged direct injection (GTDI) engine. Recent regulations requiring automotive manufacturers to increase the fuel efficiency of their vehicles has led to great technological achievements in internal combustion engines. These achievements have increased the power density of gasoline engines dramatically in the last two decades. Engine technologies such as variable valve timing (VVT), direct injection (DI), and turbocharging have significantly improved engine power-to-weight and power-to-displacement ratios. A popular trend for increasing vehicle fuel economy in recent years has been to downsize the engine and add VVT, DI, and turbocharging technologies so that a lighter more efficient engine can replace a larger, heavier one. With the added power density, thermal management of the engine becomes a more important issue. Engine components are being pushed to their temperature limits. Therefore it has become increasingly important to have a greater understanding of the parameters that affect in-cylinder temperatures and heat transfer. The proposed research will analyze the effects of engine speed, load, relative air-fuel ratio (AFR), and exhaust gas recirculation (EGR) on both in-cylinder and global temperature and heat transfer distributions. Additionally, the effect of knocking combustion and fuel spray impingement will be investigated. The proposed research will be conducted on a 3.5 L six cylinder GTDI engine. The research engine will be instrumented with a large number of sensors to measure in-cylinder temperatures and pressures, as well as, the temperature, pressure, and flow rates of energy streams into and out of the engine. One of the goals of this research is to create a model that will predict the energy distribution to the crankshaft, exhaust, and cooling system based on normalized values for engine speed, load, AFR, and EGR. The results could be used to aid in the engine design phase for turbocharger and cooling system sizing. Additionally, the data collected can be used for validation of engine simulation models, since in-cylinder temperature and heat flux data is not readily available in the literature..