Abstract
A parallel hybrid electric vehicle (PHEV) is used to investigate the fuel economy effect of the equivalent fuel consumption minimization strategy (ECMS) with the equivalent factor as the core, where the equivalent factor is the conversion coefficient between fuel thermal energy and electric energy. In the conventional ECMS strategy, the battery cannot continue to discharge when the state of charge (SOC) is lower than the target value. At this time, the motor mainly works in the battery charging mode, making it difficult to adjust the engine operating point to the high-efficiency zone during the acceleration process. To address this problem, a relationship model of the battery SOC, vehicle acceleration a, and equivalent factor S was established. When the battery SOC is lower than the target value and the vehicle demand torque is high, which makes the engine operating point deviate from the high-efficiency zone, the time that the motor spends in the power generation mode during the driving process is reduced. This enables the motor to drive the vehicle at the appropriate time to reduce the engine output torque, and helps the engine operate in the high-efficiency zone. The correction function under US06 condition was optimized by genetic algorithm (GA). The best equivalent factor MAP was obtained with acceleration a and battery SOC as independent variables, and the improved global optimal equivalent factor of ECMS was established and simulated offline. Simulation results show that compared with conventional ECMS, the battery still has positive power output even when the SOC is less than the target value. The SOC is close to the target value after the cycle condition, and fuel economy improved by 1.88%; compared with the rule-based energy management control strategies, fuel economy improved by 10.17%. These results indicate the effectiveness of the proposed energy management strategy.
Highlights
Hybrid electric vehicles (HEVs) have two major technical problems: mode switching during dynamic operation and energy distribution during steady-state operation [1].Currently, energy management control strategies mainly fall into two categories: rule-based (RB)energy management and optimization-based control strategies [2]
The state of charge (SOC) is close to the target value after the cycle condition, and fuel economy improved by 1.88%; compared with the rule-based energy management control strategies, fuel economy improved by 10.17%
In order to verify the fuel-saving effect of improved equivalent fuel consumption minimization strategy (ECMS) and battery SOC retention, the model of the whole vehicle components and the improved ECMS strategy model was established numerical model of the whole vehicle components and the improved ECMS strategy model was based on the MatLab/Simulink platform, and the backward simulation model of vehicle dynamics was established based on the MatLab/Simulink platform, and the backward simulation model of vehicle developed
Summary
Hybrid electric vehicles (HEVs) have two major technical problems: mode switching during dynamic operation and energy distribution during steady-state operation [1]. The equivalent fuel consumption minimization strategy (ECMS) based on PMP uses the local optimum to replace the global optimum of the whole operating condition to achieve real-time optimization [7]. The improved real-time equivalent energy minimum control strategy obtains the optimal torque distribution of the engine and motor under different initial SOCs on the premise of satisfying the power requirements of the vehicle. To maintain the battery power close to the target value, the conventional correction function only considers the battery SOC, and does not continue to use the energy when the battery SOC approaches SOClow At this time, the engine drives the motor to charge the battery until the SOC reaches the target value, after which the vehicle operates in the charge-sustaining (CS) mode.
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