摘要
路况信息是影响复合电源能量管理的关键因素。为提高电动汽车复合电源系统能量管理效率和延长动力电池使用寿命,提出了一种融合路况信息的车载复合电源模型预测控制方法。将未来有限时域内的车辆功率需求纳入控制问题,建立能量管理优化模型,利用二次规划方法对目标函数进行滚动最优求解。与基于模糊控制的能量管理策略相比,模型预测控制策略下的超级电容制动能量回收能力提升了13.7%,动力电池容量衰减速率降低了15.4%。结果表明,融合路况信息的模型预测控制方法能够提高超级电容利用效率,延长动力电池使用寿命,提升复合电源系统能量管理效率。
Route information is a key factor affecting the energy management of hybrid energy storage system(HESS).For the purpose of improving the energy management efficiency of HESS and increase the battery lifespan,a model predictive control(MPC) method for HESS based on route information was proposed.The power demand in the future limited time domain was included in the control problem,and the energy management optimization model was established.The quadratic programming method was used to perform the rolling optimal solution of the objective function.Compared with the fuzzy control energy management strategy,the supercapacitor braking energy recovery capability under the MPC was increased by 13.7%,and the power battery capacity degradation rate was reduced by 15.4%.The results show that the MPC method based on route information can improve the utilization efficiency of the supercapacitor,prolong the service life of the power battery,and improve the energy management efficiency of the HESS.
作者
尹炳琪
马彬
杨朝红
陈晓薇
YIN Bing-qi;MA Bin;YANG Zhao-hong;CHEN Xiao-wei(School of Mechanical and Electrical Engineering,Beijing Information Science and Technology University,Beijing 100192,China;Collaborative Innovation Center of Electric Vehicles in Beijing,Beijing 100192,China)
出处
《电源技术》
CAS
北大核心
2020年第4期557-561,共5页
Chinese Journal of Power Sources
基金
国家自然科学基金青年基金项目(51608040)
北京市自然科学基金青年项目(3174049)
北京信息科技大学科研重点培育项目(5211910942)
北京信息科技大学“勤信人才”培育计划项目(QXTCPC201701)
研究生科技创新项目(5121911047)。
关键词
复合电源
路况信息
模型预测控制
容量衰减
hybrid energy storage system
route information
model predictive control
capacity degradation