检索结果-南通市图书馆

Automotive Innovation 2023年第3期6卷 492-507页

作者： Kegang Zhao Kunyang He Zhihao Liang Maoyu Mai School of Mechanical and Automotive Engineering South China University of TechnologyGuangzhou510610China

The study of series–parallel plug-in hybrid electric vehicles(PHEVs)has become a research hotspot in new energy vehicles.The global optimal Pareto solutions of energy management strategy(EMS)play a crucial role in the development of PHEVs.This paper presents a multi-objective global optimization algorithm for the EMS of PHEVs.The algorithm combines the Radau Pseudospectral Knotting Method(RPKM)and the Nondominated Sorting Genetic Algorithm(NSGA)-II to optimize both energy conservation and battery lifespan under the suburban driving conditions of the New European Driving Cycle.The driving conditions are divided into stages at evident mode switching points and the optimal objectives are computed using RPKM.The RPKM results serve as the fitness values in iteration through the NSGA-II method.The results of the algorithm applied to a PHEV simulation show a 26.74%–53.87%improvement in both objectives after 20 iterations compared to the solutions obtained using only RPKM.The proposed algorithm is evaluated against the weighting dynamic programming and is found to be close to the global optimality,with the added benefits of faster and more uniform solutions.

关键词： Plug-in hybrid electric vehicles energy management strategy Multi-objective optimization Global optimization NSGA-II Radau pseudospectral knotting method

Speed planning and energy management strategy of hybrid electric vehicles in a car-following scenario

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Control Theory and Technology 2022年第2期20卷 185-196页

作者： Shengyan Hou Hong Chen Yu Zhang Jinwu Gao State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022JilinChina Department of Control Science and Engineering Jilin UniversityChangchun 130025JilinChina Department of Control Science and Engineering Tonji UniversityShanghai 200092China Suzhou Zhito Technology Co. Ltd.Suzhou 215129JiangsuChina

The development of intelligent connected technology has brought opportunities and challenges to the design of energy management strategies for hybrid electric vehicles.First,to achieve car-following in a connected environment while reducing vehicle fuel consumption,a power split hybrid electric vehicle was used as the research object,and a mathematical model including engine,motor,generator,battery and vehicle longitudinal dynamics is established.Second,with the goal of vehicle energy saving,a layered optimization framework for hybrid electric vehicles in a networked environment is proposed.The speed planning problem is established in the upper-level controller,and the optimized speed of the vehicle is obtained and input to the lower-level controller.Furthermore,after the lower-level controller reaches the optimized speed,it distributes the torque among the energy sources of the hybrid electric vehicle based on the equivalent consumption minimum strategy.The simulation results show that the proposed layered control framework can achieve good car-following performance and obtain good fuel economy.

关键词： Hybrid electric vehicle Car-following Speed planning energy management strategy

energy management strategy Considering Multi-time-scale Operational Modes of Batteries for the Grid-connected Microgrids Community

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CSEE Journal of Power and energy Systems 2020年第1期6卷 111-121页

作者： Xiaowen Xing Lili Xie Hongmin Meng Xin Guo Lei Yue Josep M.Guerrero Department of Electrical Engineering Northwestern Polytechnical UniversityXi’an 710072China State Grid Information and Telecommunication Group Ltd.Co. Beijing 102211China State Grid Beijing Fengtai Electric Power Supply Company Beijing 100073China China Electric Power Research Institute Beijing 100192China Department of energy Technology Aalborg UniversityAalborg9220Denmark

The advantages and promoting applications of the microgrids community(MGC)allows for a critical step being taken toward a smart grid.An energy management strategy(EMS)is essential to intelligently coordinate the operations of the MGC.This paper presents a multi-time-scale EMS consid-ering battery operational modes for grid-connected MGCs.The proposed strategy consists of two modules:day-ahead integrated optimization and realtime distributed compensation.The first module aims to minimize the operational cost of the MGC considering battery free-overcharging protecting.This problem is solved by the mixed integer linear programming(MILP)sim-ulating two charging/discharging modes:limited-current mode and constant-voltage mode.The second module is installed in local MGs to correct the optimizing deviations of the day-ahead static scheduling,which are caused by predicting errors of renewable energy and loads.The main contribution of this work is integrating the advantages of global optimization of the centralized method and the fast computing speed of the distributed method.Experimental results prove the proposed EMS is feasible and effective.The computing time at each updating step is reduced by 75%on average,which has the potential to be adopted in engineering.

关键词： Day-ahead optimization energy management strategy forecast errors microgrids community realtime compensation strategy

energy management strategy based on dynamic programming with durability extension for fuel cell hybrid tramway

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Railway Engineering Science 2021年第3期29卷 299-313页

作者： Shiyong Tao Weirong Chen Rui Gan Luoyi Li Guorui Zhang Ying Han Qi Li School of Electrical Engineering Southwest Jiaotong UniversityChengdu 610031China

This paper proposes an energy management strategy for a fuel cell(FC)hybrid power system based on dynamic programming and state machine strategy,which takes into account the durability of the FC and the hydrogen consumption of the system.The strategy first uses the principle of dynamic programming to solve the optimal power distribution between the FC and supercapacitor(SC),and then uses the optimization results of dynamic programming to update the threshold values in each state of the finite state machine to realize real-time management of the output power of the FC and SC.An FC/SC hybrid tramway simulation platform is established based on RTLAB real-time simulator.The compared results verify that the proposed EMS can improve the durability of the FC,increase its working time in the high-efficiency range,effectively reduce the hydrogen consumption,and keep the state of charge in an ideal range.

关键词： Hydrogen Fuel cell Supercapacitor energy management strategy Tramway

Multi-mode energy management strategy for hydraulic hub-motor auxiliary system based on improved global optimization algorithm

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2020年第10期63卷 2082-2097页

作者： ZENG XiaoHua WU ZiQiao WANG Yue SONG DaFeng LI GuangHan State Key Laboratory of Automobile Simulation and Control Jilin UniversityChangchun 130025China

Heavy commercial vehicles equipped with a hydraulic hub-motor auxiliary system(HHMAS)often operate under complex road conditions.Selecting appropriate operating mode and realizing reasonable energy management to match unpredictable road conditions are the keys to the driving performance and fuel economy of HHMAS.Therefore,a multi-mode energy management strategy(MM-EMS)based on improved global optimization algorithm is proposed in this study for HHMAS.First,an improved dynamic programming(DP)algorithm for HHMAS is developed.This improved DP algorithm considers the effect of SOC and vehicle speed,thereby preventing the calculation results from falling into local optimization.This algorithm also reduces the dimension of the control variable data grid,and the calculation time is reduced by 35%without affecting the accuracy.Second,a MM-EMS with hierarchical control is proposed.This strategy extracts the optimal control rules from the results of the improved DP algorithm.Then it divides the system’s operating region into two types,namely,single-mode working region and mixedmode working region.In the single-mode working region,mode switching is realized through fixed thresholds.In the mixedmode working region,a linear quadratic regulator(LQR)is adopted to determine a target mode and realize SOC tracking control.Finally,the designed MM-EMS is verified separately in offline simulation and hardware-in-the-loop(HIL)under actual vehicle test cycles.Simulation results show that the results between HIL and offline simulation are largely coincidence.Besides,in comparison with the engine optimal control strategy,the designed MM-EMS can achieve an approximate optimal control,with oil savings of 3.96%.

关键词： hydraulic hub-motor auxiliary system energy management strategy global optimization hierarchical control

Deep reinforcement learning based energy management strategy for fuel cell/battery/supercapacitor powered electric vehicle

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Green energy and Intelligent Transportation 2022年第2期1卷 97-111页

作者： Jie Wang Jianhao Zhou Wanzhong Zhao College of energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

Vehicles using a single fuel cell as a power source often have problems such as slow response and inability to recover braking energy.Therefore,the current automobile market is mainly dominated by fuel cell hybrid vehicles.In this study,the fuel cell hybrid commercial vehicle is taken as the research object,and a fuel cell/battery/supercapacitor energy topology is proposed,and an energy management strategy based on a double-delay deep deterministic policy gradient is designed for this topological structure.This strategy takes fuel cell hydrogen consumption,fuel cell life loss,and battery life loss as the optimization goals,in which supercapacitors play the role of coordinating the power output of the fuel cell and the battery,providing more optimization ranges for the optimization of fuel cells and batteries.Compared with the deep deterministic policy gradient strategy(DDPG)and the nonlinear programming algorithm strategy,this strategy has reduced hydrogen consumption level,fuel cell loss level,and battery loss level,which greatly improves the economy and service life of the power system.The proposed EMS is based on the TD3 algorithm in deep reinforcement learning,and simultaneously optimizes a number of indicators,which is beneficial to prolong the service life of the power system.

关键词： Deep reinforcement learning energy management strategy Fuel cell Hybrid electric vehicle TD3

Control algorithm and energy management strategy for extended range electric tractors

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Agricultural and Biological Engineering 2017年第5期10卷 35-44页

作者： Xu Liyou Zhang Junjiang Liu Mengnan Zhou Zhili Liu Chengqiang College of Vehicle and Traffic Engineering Henan University of Science and TechnologyLuoyang 471003China Shandong Shifeng Group Co. Ltd.Liaocheng 252800China

It is difficult to make full use of the electrical energy of the power battery for extended-range electric tractors because the battery’s state of charge may be relatively high at the end of the running mileage.To address this situation,this paper aimed to study the control parameter adjustment in relation to the power battery’s electrical consumption and the diesel engine’s fuel consumption energy management strategy.Based on the AVL-Cruise simulation platform,the vehicle model of the tractor was established,and the control module of AVL-Cruise was used to compile the energy management strategy.In order to verify the superiority of the proposed strategy,the contrast strategy was employed in terms of the diesel engine start and stop control plus fixed point energy management strategy(FPEMS).The applicability of the proposed strategy was tested through continuous transfer operation and the small area deep loosening operation.The simulation results show that the proposed strategy was of good applicability.Compared with the FPEMS,the fuel consumption reduced significantly,and the electrical consumption of the power battery increased obviously.

关键词： extended-range electric tractor parameter adjustment energy management strategy simulation analysis

A Predictive energy management Strategies for Mining Dump Trucks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

energy Engineering 2024年第3期121卷 769-788页

作者： Yixuan Yu Yulin Wang Qingcheng Li Bowen Jiao College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China

The plug-in hybrid vehicles(PHEV)technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks.Meanwhile,plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies(EMS).Therefore,a series hybrid system is constructed based on a 100-ton mining dump truck in this paper.And inspired by the dynamic programming(DP)algorithm,a predictive equivalent consumption minimization strategy(P-ECMS)based on the DP optimization result is proposed.Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm,the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor(EF).Finally,applying the equivalent consumption minimization strategy(ECMS)realizes real-time control.The simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km,which is 10.9%less than that of the common CDCS strategy(169.3 L/100 km),and achieves 99.47%of the fuel saving effect of the DP strategy(150 L/100 km).

关键词： Mining dump truck energy management strategy plug-in hybrid electric vehicle equivalent consumption minimization strategy dynamic programming

Simulation research of energy management strategy for dual mode plug-in hybrid electrical vehicles

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Chongqing University 2017年第2期16卷 59-71页

作者：李训明 liu hui xin hui-bin yan zheng-jun zhang zhi-peng liu bei School of Mechanical Engineering Beijing Institute of Technology Beijing 100081 P. R. China

In this paper, a plug-in hybrid electrical vehicle(PHEV) is taken as the research object, and its dynamic performance and economic performance are taken as the research goals. Battery charge-sustaining(CS) period is divided into power mode and economy mode. energy management strategy designing methods of power mode and economy mode are proposed. Maximum velocity, acceleration performance and fuel consumption are simulated during the CS period in the AVL CRUISE simulation environment. The simulation results indicate that the maximum velocity and acceleration time of the power mode are better than those in the economy mode. Fuel consumption of the economy mode is better than that in the power mode. Fuel consumption of PHEV during the CS period is further improved by using the methods proposed in this paper, and this is meaningful for research and development of PHEV.

关键词： plug-in hybrid electrical vehicle power mode eco mode energy management strategy model and simulation

Research on System Control and energy management strategy of Flux-Modulated Compound-Structure Permanent Magnet Synchronous Machine

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

CES Transactions on Electrical Machines and Systems 2017年第2期1卷 100-108页

作者： Jiaqi Liu Chengde Tong Zengfeng Jin Guangyuan Qiao Ping Zheng school of Electrical Engineering and Automation Harbin Institute of TechnologyHarbinChina SAIC Motor ShanghaiChina

The flux-modulated compound-structure permanent magnet synchronous machine (CS-PMSM), composed of a brushless double rotor machine (DRM) and a conventional permanent magnet synchronous machine (PMSM), is a power split device for plug-in hybrid electric vehicles. In this paper, its operating principle and mathematical model are introduced. A modified current controller with decoupled state feedback is proposed and verified. The system control strategy is simulated in Matlab, and the feasibility of the control system is proven. To improve fuel economy, an energy management strategy based on fuzzy logic controller is proposed and evaluated by the Urban Dynamometer Driving Schedule (UDDS) drive cycle. The results show that the total energy consumption is similar to that of Prius 2012.

关键词： CS-PMSM energy management strategy flux-modulated hybrid electric vehicle system control