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Multi-objective Optimization of EREV Control Strategy with Pointer Hybrid Optimization Algorithm
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AI
DOI：10.2112/SI83-118.1.png)
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摘要
En 中文
EREVs (extended-range electric vehicles) are powered by range extenders and power batteries which have their own operation modes and appropriate control strategies should be adopted to minimize the total energy loss. The improved constant power control strategy is proposed and a velocity threshold is established in EV mode to prevent excessive battery discharge and excessive current to extend battery life. The multi objective optimization algorithm is applied to achieve the optimal fuel consumption, energy consumption and maximum velocity of EREVs. The multi-objective functions, optimization variables and constraints are defined. This paper selects final drive ratio, maximum & minimum SOC (state of charge), and velocity threshold of a certain EREV as the optimization objects and optimizes EREV performance with Pointer hybrid optimization algorithm, thereby reducing the cost of cyclic fuel consumption and energy consumption in the running process. The simulation results show that electric energy consumption increases by 36% while fuel consumption decreases by 98%, which demonstrates the feasibility and effectiveness of optimization objects, optimization variables and optimization strategies adopted in this paper.
Keyword:
Pointer hybrid optimization algorithm
control strategy
multi-objective optimization
extended-range electric vehicles
