多目标遗传算法的电动汽车电-液复合制动系统控制策略优化

Multi-objective optimization of the control strategy of EVs electric-hydraulic composite braking system with genetic algorithm

控制策略的优化对于电动汽车性能的改善至关重要,电动汽车电-液复合制动控制策略优化的目的是要在满足制动稳定性的前提下尽可能多地回收制动能量。通过引入多目标遗传算法,以制动稳定性及制动能量回收效率为目标,在多个约束条件下对影响电-液复合制动控制策略的多个关键参数进行协同优化,并通过电动汽车再生制动软件仿真平台对优化结果进行了验证。结果表明,优化目标具有很好的收敛性,且优化后的控制策略能够有效提高再生制动能量的回收效率。

Optimization of the control strategy plays an important role in improving the performance of electric vehicles. In order to improve the braking stability and recover the braking energy, a Multi-Objective Genetic Algorithm（MOGA） is applied to optimize the key parameters in the control strategy of Electric Vehicles （EVs） electro-hydraulic composite braking system. Various limita- tions are considered in the optimization process and the optimization results are verified by a software simulation platform of elec- tric vehicle regenerative braking system in typical brake conditions. The results show that optimization objectives achieved a good astringency, and the optimized control strategy can increase the brake energy recovery effectively under the condition of ensuring the braking stability.