考虑全寿命周期成本的PHEB控制策略

PHEB control strategy considering life-cycle cost

考虑电池寿命提前结束更换电池导致全寿命周期成本增加,针对某款功率分流式插电式混合动力客车,建立电池寿命模型和整车动力学模型。为精确估计动力电池健康状态,基于实车运行数据,结合主成分分析法提取电池健康因子,建立遗传算法优化的径向基神经网络动力电池寿命模型。考虑到控制策略对电池寿命和能耗的影响,建立包含能耗成本和电池更换成本的全寿命周期成本模型,制定模型预测控制策略。仿真结果表明,与以能耗成本为目标的优化相比,以全寿命周期成本为目标的优化使能耗成本仅增加了5.8%,电池寿命衰减降低了15.2%,整车使用过程中电池无需更换,综合成本降低了8.5%。达到车辆报废时,电池寿命刚好结束,降低了全寿命周期成本的目的。

In view of the fact that the battery life ends ahead of schedule,which leads to the battery replacement,which increases the life-cycle cost,a battery life model and a vehicle dynamics model are established for a certain plug-in hybrid electric bus(PHEB)with power dividing.In order to accurately estimate the state of health(SOH)of power battery,the principal component analysis(PCA)is adopted to extract the battery health factors,so as to establish a power battery life model based on RBF neural network optimized by genetic algorithm(GA).The model is based on the operation data of real vehicle.For the control strategy has an influence on battery life and energy consumption,a life-cycle cost model including energy consumption cost and battery replacement cost is established.In addition,a model prediction control strategy is developed.The simulation results show that,in comparison with the optimization based on the energy consumption cost,the optimization based on the life-cycle cost only increases the energy consumption cost by 5.8%and reduces the battery life attenuation by 15.2%.It means that the battery does not need to be replaced during the use of the vehicle,and the overall cost is reduced by 8.5%.When the vehicle is scrapped,the life of its battery is just over,which achieves the purpose of reducing the cost of life-cycle.