A study on Optimizing SHEV Components Specifications and Control Parameter Values for the Reduction of Fuel Consumption by Using a Genetic Algorithm
2022-01-0817
03/29/2022
- Event
- Content
- For series hybrid electric vehicles (SHEV), the electric motor is responsible for the propulsion, and the engine drives the only generator to supply electric power. SHEVs set a control strategy to make the engine run near the fixed operating point with high thermal efficiency, thereby effectively reducing fuel consumption. The powertrain system of HEV is more complex than that of internal combustion engine, and it is time-consuming to obtain the optimal specification values and controls. Therefore, automatic optimization methods are required nowadays. We used Genetic Algorithm (GA) as the optimization method and optimize powertrain specifications and control parameter values to reduce fuel consumption. The results show that it is an effective optimization method. In this research, we use a SHEV model constructed in MATLAB/Simulink and optimize the maximum torque of the motor, the capacity of the battery, and the control parameter values for starting and stopping the engine. Then, the degree of influence of each optimized parameter on the fuel consumption is analyzed. The components which have high sensitivity on fuel consumption are the battery capacity, the maximum torque of the motor and thresholds value for engine off. As a result of optimization by GA, fuel consumption was reduced by 1.1% compared to the baseline. We are also verifying whether manual calibration of parameters or GA is the more efficient method. Manual calibration of parameters means setting all possible combinations of parameters, calculating the fuel consumption value for each combination and finding the minimum value. As it shows in the result, optimization can be achieved in less time with GA.
- Citation
- Cao, X., Asano, N., Yamagishi, T., Yamaguchi, K. et al., "A study on Optimizing SHEV Components Specifications and Control Parameter Values for the Reduction of Fuel Consumption by Using a Genetic Algorithm," SAE Technical Paper 2022-01-0817, 2022, .