随机混杂预测控制的插电式混合动力系统能量管理策略优化机理

项目名称： 随机混杂预测控制的插电式混合动力系统能量管理策略优化机理

项目编号： No.51505086

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 林歆悠

作者单位： 福州大学

项目金额： 20万元

中文摘要： 以进一步提高插电式混合动力汽车节能减排效果为目标，综合考虑不同行驶里程以及随机多变行驶工况的影响，针对插电式多模混合动力系统，开展随机混杂预测控制的能量管理策略优化机理研究，这属于该领域的发展趋势及热点。为解决PHEV不同期望行驶里程的最佳电量消耗模式对实际随机工况的适应性问题，将行驶中的PHEV视为动态系统，构建基于混杂动态理论能量管理策略理论框架及性能评价平台，根据ECMS思想，探索不同期望行驶里程的等效因子与电量消耗模式边际成本间的关系，形成判断节能盈亏边界的运行模式切换控制方法，以及提出基于由行程能量率EDR与等效因子构成的油电价值量成本模型的SOC实时优化控制方法，在此基础上，结合驾驶员随机统计规律及AFSMC油电价值量控制算法，提出SH-MPC实时优化能量管理策略，形成一套新型的PHEV能量管理策略优化理论方法，为实现我国自主研发高效、节能、环保的PHEV提供坚实的理论依据。

中文关键词： 插电式混合动力系统；能量管理策略；随机模型预测控制；混杂动态系统

英文摘要： The project plan focuses on how to improve the effectiveness of energy saving and emission reduction for the plug-in hybrid electric vehicle (PHEV), considering the influence of factors, such as the different mileage and random variable driving conditions, based on the structure of multi-mode system for plug-in hybrid electric vehicle, and optimization mechanism of energy management strategy based on stochastic hybrid model predictive control is proposed, this investigation belongs to the field of development trend and frontier. To solve the optimum charge depleting mode of adaptability to various random working conditions for PHEV under different target driving mileage, the driving PHEV is designed as a dynamic system, so build a theoretical framework of power management strategy based on the hybrid dynamic system and performance evaluation simulation platform. According to the idea of ECMS, acquiring the relationship between the equivalent factor and marginal costs of charge depleting mode under different target driving mileage, and then to form the method of operation mode switch control based on judging the boundary of energy saving or cost. And the SOC real-time optimal control method based on the value tradeoff between fuel and electricity control model which is constituted by EDR (Energy to Distance Ratio) and equivalent factor. On the basis, combined with the driver random statistical rule and the value control algorithm of fuel and electricity based on AFSMC (Adaptive Fuzzy Sliding Mode Control) theory, the real-time optimization of energy management strategy based on stochastic hybrid model predictive control is proposed, and finally, to form a theoretical method for development of plug-in hybrid electric vehicle energy management strategy real-time control. The proposed plan provides a theoretical method to support the independent research of the new generation plug-in hybrid electric vehicles with features of high-efficiency, energy-saving and eco-friendliness.

英文关键词： Plug-in Hybrid Electric System ;Energy Management Strategy ;Stochastic Model Predictive Control;Hybrid Dynamic System