为实现混合动力两栖车综合效率最优,提出一种功率协调预测控制策略.该策略旨在协同优化能量管理策略与车速控制策略之间的耦合关系.针对车速预测模型失配的问题,提出利用极限学习机进行实时误差预测,并通过预测值进行预测模型校正.设计模型预测控制器实现能量管理与车速控制的实时优化控制,并通过仿真进行验证.研究结果表明:提出的策略相较于传统的基于模型预测控制的能量管理策略能够降低等效燃油消耗、荷电状态(State of Charge,SOC)标准差、母线电压标准差和电池容量衰退,降低幅度分别为9.35％、59.63％、15.79％和45.33％;通过有无模型校正的功率协调预测控制对比,表明通过模型校正可实现等效燃油消耗、SOC标准差、母线电压标准差和电池容量衰退分别降低6.95％、25.91％、13.46％和24.07％,体现了所提出的基于极限学习机模型校正的功率协调预测控制在提升燃油经济性、维持电气系统稳定性和降低电池损耗方面的优越性.
Power Coordinated Predictive Control of Hybrid Amphibious Vehicle with Model Mismatch
To achieve the optimal comprehensive efficiency of hybrid amphibious vehicle,a power coordinated predictive control strategy is proposed.This strategy deals with the coupling relationship between energy management strategy and longitudinal control strategy through collaborative optimization.Aiming at the mismatch of prediction model,an extreme learning machine(ELM)is used for real-time error prediction,and the prediction model is corrected through the predicted value.A model predictive controller(MPC)is designed for the real-time optimal control of energy management and longitudinal control,and it is verified by simulation.The results show that,compared with the traditional energy management strategy based on MPC,the proposed strategy can be used to reduce the equivalent fuel consumption,state-of-charge(SOC)standard deviation,bus voltage standard deviation and battery capacity fading by 9.35％,59.63％,15.79％and 45.33％,respectively.By comparing the power coordinated predictive control with and without model correction,it shows that the equivalent fuel consumption,SOC standard deviation,bus voltage standard deviation and battery capacity fading can be reduced by 6.95％,25.91％,13.46％and 24.07％,respectively,through model correction,which reflects the superiority of the power coordinated predictive control based on ELM model correction in improving the fuel economy,maintaining the stability of electrical system and reducing the battery consumption.
万方数据
维普
