机械工程学报
機械工程學報
궤계공정학보
Journal of Mechanical Engineering
2015年
16期
11-21
,共11页
混合动力电动汽车%巡航控制%非线性模型预测控制
混閤動力電動汽車%巡航控製%非線性模型預測控製
혼합동력전동기차%순항공제%비선성모형예측공제
hybrid electric vehicle%cruise control%nonlinear model predictive control
针对混合动力汽车巡航过程的跟踪安全性和燃油经济性的优化问题,提出基于非线性模型预测理论的混合动力汽车预测巡航控制策略。考虑发动机燃油效率及电机效率的非线性,提出离线安全与经济性协调预测优化与在线查表相结合的控制系统总体结构。基于车辆行驶距离空间域,建立具有动力学非线性、系统离散性的混合动力系统巡航控制的广义纵向动力学系统模型。以驾驶员稳定跟踪为约束,设计安全性与经济性协调的多性能指标数学量化函数。基于非线性模型预测理论,提出混合动力汽车预测巡航的多目标优化控制算法。为验证所提控制算法的有效性与综合优势,建立前向仿真平台及实车试验平台,仿真及实车结果都表明,所提出的预测巡航控制算法相比常规算法在跟踪安全性和燃油经济性方面具有较大优势。
針對混閤動力汽車巡航過程的跟蹤安全性和燃油經濟性的優化問題,提齣基于非線性模型預測理論的混閤動力汽車預測巡航控製策略。攷慮髮動機燃油效率及電機效率的非線性,提齣離線安全與經濟性協調預測優化與在線查錶相結閤的控製繫統總體結構。基于車輛行駛距離空間域,建立具有動力學非線性、繫統離散性的混閤動力繫統巡航控製的廣義縱嚮動力學繫統模型。以駕駛員穩定跟蹤為約束,設計安全性與經濟性協調的多性能指標數學量化函數。基于非線性模型預測理論,提齣混閤動力汽車預測巡航的多目標優化控製算法。為驗證所提控製算法的有效性與綜閤優勢,建立前嚮倣真平檯及實車試驗平檯,倣真及實車結果都錶明,所提齣的預測巡航控製算法相比常規算法在跟蹤安全性和燃油經濟性方麵具有較大優勢。
침대혼합동력기차순항과정적근종안전성화연유경제성적우화문제,제출기우비선성모형예측이론적혼합동력기차예측순항공제책략。고필발동궤연유효솔급전궤효솔적비선성,제출리선안전여경제성협조예측우화여재선사표상결합적공제계통총체결구。기우차량행사거리공간역,건립구유동역학비선성、계통리산성적혼합동력계통순항공제적엄의종향동역학계통모형。이가사원은정근종위약속,설계안전성여경제성협조적다성능지표수학양화함수。기우비선성모형예측이론,제출혼합동력기차예측순항적다목표우화공제산법。위험증소제공제산법적유효성여종합우세,건립전향방진평태급실차시험평태,방진급실차결과도표명,소제출적예측순항공제산법상비상규산법재근종안전성화연유경제성방면구유교대우세。
Focusing on the safety and fuel economy improvement of hybrid electric vehicle(HEV)during the adaptive cruise control, a predictive HEV cruise control strategy is proposed based on nonlinear model predictive control method. Considering the nonlinearities of engine fuel efficiency and motor electricity efficiency, the control architecture combines offline predictive optimization of tracking ability and fuel efficiency, and online integration based on offline results is designed. Considering the nonlinearities and discrete characteristics of vehicle dynamics, a position based hybrid longitudinal inter-vehicle dynamics model is developed. Based on the terminal constraints of stable tracking, a coordinated cost function of tracking safety and fuel economy is formulated. Utilizing the nonlinear model predictive control method, the multi-objective optimization control algorithm is developed. To validate the comprehensive performances and advantages of proposed algorithm, both simulation and experiments are implemented. Simulation and experiment results show that, the proposed algorithm has better integrated performances of tracking ability and fuel economy compared with conventional algorithms.