Research on Control Strategy for a Battery Thermal Management System for Electric Vehicles Based on Secondary Loop Cooling

Abstract

A secondary loop cooling battery thermal management system is designed, and then, a phased control strategy for adjusting the compressor speed according to the battery temperature interval is proposed. On this basis, the compressor speed as the decision variable, and the energy consumption of the compressor and the aging losses of the battery are as the optimization goals, which constitute a multi-objective optimization model, and a genetic algorithm is adopted to solve it. Under different weight coefficients, the Pareto Frontier of the energy consumption of the compressor and the aging losses of the battery are established. The simulation analysis is conducted on high speed dynamic conditions at an ambient temperature of 30 °C. The effects of coolant flow rate and compressor speed on battery pack temperature rise and temperature uniformity are analyzed. The simulation results show that the energy consumption of the phased control strategy is reduced by 10.7% compared with the traditional constant compressor speed control strategy under the same conditions. Under different weight coefficients, different simulation results and control strategies can be obtained, and results show that the maximum temperature and temperature uniformity can meet the requirements. There is a contradiction between the energy consumption of compressor and the aging losses of battery, but both them are highly sensitive. According to the Pareto Frontier curve, when the weight coefficient is 0.17, a balanced control strategy can be obtained, which can reduce the battery aging losses of 61.8% by only sacrificing 9.22% of the vehicle driving mileage.

Keywords

• Battery thermal management
• control strategy
• genetic algorithm
• lithium-ion cell
• multi-objective optimization
• secondary loop cooling