中国机械工程
中國機械工程
중국궤계공정
CHINA MECHANICAl ENGINEERING
2012年
7期
869-874
,共6页
客车%混合动力传动%工况识别%功率均衡
客車%混閤動力傳動%工況識彆%功率均衡
객차%혼합동력전동%공황식별%공솔균형
city bus%hybrid electric powertrain%driving cycle recognition%power balancing
为进一步提高新型混联式混合动力客车燃油经济性,根据城市循环工况的特点选定了四种典型的城市工况,采用学习向量量化（LVQ）神经网络模型对各工况特征参数进行训练学习以进行实时工况识别,结合基于动态规划的全局优化结果来提取功率均衡控制规则并存储于控制模块中以供不同工况选择,制定了基于工况识别的控制策略。以MATLAB/Simulink为平台建立基于工况识别的控制策略整车前向仿真模型,仿真结果表明,与普通控制策略相比,采用基于工况识别的控制策略的燃油经济性提高7%。
為進一步提高新型混聯式混閤動力客車燃油經濟性,根據城市循環工況的特點選定瞭四種典型的城市工況,採用學習嚮量量化（LVQ）神經網絡模型對各工況特徵參數進行訓練學習以進行實時工況識彆,結閤基于動態規劃的全跼優化結果來提取功率均衡控製規則併存儲于控製模塊中以供不同工況選擇,製定瞭基于工況識彆的控製策略。以MATLAB/Simulink為平檯建立基于工況識彆的控製策略整車前嚮倣真模型,倣真結果錶明,與普通控製策略相比,採用基于工況識彆的控製策略的燃油經濟性提高7%。
위진일보제고신형혼련식혼합동력객차연유경제성,근거성시순배공황적특점선정료사충전형적성시공황,채용학습향량양화（LVQ）신경망락모형대각공황특정삼수진행훈련학습이진행실시공황식별,결합기우동태규화적전국우화결과래제취공솔균형공제규칙병존저우공제모괴중이공불동공황선택,제정료기우공황식별적공제책략。이MATLAB/Simulink위평태건립기우공황식별적공제책략정차전향방진모형,방진결과표명,여보통공제책략상비,채용기우공황식별적공제책략적연유경제성제고7%。
To improve fuel economy of a novel series-parallel hybrid electric bus（SPHEB） further,and four types of roadway were selected to present the characteristics of city driving cycle,a learning vector quantization neural network was adopted to learn and identify the driving cycle,and integrated with the power balancing strategy which was derived from the results of global optimization based on dynamic programming.So a driving cycle adaption control strategy was proposed.To validate the proposed strategy to be effective and reasonable,a forward model was built based on MATLAB Simulink,and the results were compared to that of normal strategy.The simulation results demonstrate that the proposed strategy can be more efficient and the improvement of fuel economy is up to 7%.
