Shunsuke Okubo

Fuzzy Gain-Scheduling Proportional–Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle

With the increased emphasis on improving fuel economy and reducing emissions, hybrid electric vehicles (HEVs) have emerged as very strong candidates to achieve these goals. The power-split hybrid system, which is a complex hybrid powertrain, exhibits great potential to improve fuel economy by determining the most efficient regions for engine operation and thereby high-voltage (HV) battery operation to achieve overall vehicle efficiency optimization. To control and maintain the actual HV battery power, a sophisticated control system is essential, which controls engine power and thereby engine speed to achieve the desired HV battery maintenance power. Conventional approaches use proportional-integral (PI) control systems to control the actual HV battery power in power-split HEV, which can sometimes result in either overshoots of engine speed and power or degraded response and settling times due to the nonlinearity of the power-split hybrid system. We have developed a novel approach to intelligently controlling engine power and speed behavior in a power-split HEV using the fuzzy control paradigm for better performances. To the best of our knowledge, this is the first reported use of the fuzzy control method to control engine power and speed of a power-split HEV in the applied automotive field. Our approach uses fuzzy gain scheduling to determine appropriate gains for the PI controller based on the systems operating conditions. The improvements include elimination of the overshoots as well as approximate 50% faster response and settling times in comparison with the conventional linear PI control approach. The improved performances are demonstrated through simulations and field experiments using a ford escape hybrid vehicle.

Rule-Based Fuzzy Gain-Scheduling PI Controller to Improve Engine Speed and Power Behavior in a Power-split Hybrid Electric Vehicle

Environmental awareness has resulted in greater emphasis on developing more environmentally friendly and fuel efficient vehicles. Hybrid electric vehicles (HEVs) have been considered a viable option towards achieving these goals. Ford Motor Company developed a full hybrid electric vehicle with an e-CVT (electronically controlled continuously variable transmission) or power-split hybrid powertrain with an integrated motor and generator. The power-split hybrid system uses planetary gear sets to connect an engine, a generator, and a motor. This HEV powertrain exhibits great potential to improve fuel economy by enabling the engine to operate at its most efficient region independent of the vehicle speed. To achieve fuel economy improvements of the power-split hybrid system, high-voltage (HV) battery power management is critical. To control actual HV battery power in such vehicles, a sophisticated control system is essential which controls engine power and thereby engine speed to achieve the desired HV battery maintenance power. Conventional approaches use proportional-integral (PI) control systems to control the actual HV battery power in power-split hybrid system, which can sometimes result in either overshoots of engine speed and power or degraded response and settling times due to the nonlinearity of the power-split hybrid system. Such an overshoot is often objectionable to customers, which see engine speed overshoots as disconnect between the drivers request and the engine response. This issue comes from the fact that a complete high fidelity mathematical model for the power-split HEV system along with the environmental effects cannot be accurately modeled inside the controller. Therefore, a controller adaptable to nonlinear behavior and not requiring detailed knowledge of mathematical model of the plant is required to address such issues. Fuzzy control approaches can provide a way to cope with the limitations of the conventional controllers. We have developed a fuzzy control approach with minimal rules to intelligently control engine power and speed behavior in a powersplit HEV. This approach uses selective minimal rule-based fuzzy gain-scheduling to determine appropriate gains for the PI controller based on the systems operating conditions. The improvements result in the reduction of the overshoots without compromising systems response and settling times in comparison with the conventional linear PI controller. This paper describes the power-split hybrid vehicles powertrain system and key subsystems. It also describes minimal rule-based fuzzy gain-scheduling PI controller and the formulation of minimal fuzzy rules required to achieve the desired behavior. This minimal rule-based fuzzy controller was implemented in a Ford Escape hybrid vehicle and was evaluated in the vehicle test environment for a comparative analysis of the results to show its effectiveness. The results clearly demonstrate that the designed minimal rule based fuzzy gains scheduling controller is capable of significantly improving the engine speed and power behavior in a power-split HEV without compromising the systems response and settling times