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A Predictive Energy Management Strategies for Mining Dump Trucks

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

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Energy Management of a Parallel plug-in hybrid electric vehicle Based on SA-PSO Algorithm

Energy Management of a Parallel Plug-In Hybrid Electric Vehi...

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第36届中国控制会议

作者： Ping Li Naxin Cui Zhuo Kong Chenghui Zhang School of Control Science and Engineering Shandong University

ISBN: (纸本)9781538629185

In this paper,an intelligent energy management strategy is introduced to improve the fuel economy of a parallel plug-in hybrid electric vehicle（PHEV）.Based on the dynamic system analysis,a fuzzy controller is designed for the energy management of PHEV.Then the combination of Simulated Annealing and Particle Swarm Optimization（SA-PSO） is applied to achieve the optimal parameters of the fuzzy controller.To improve the adaptability of the strategy under different road conditions,the hybrid driving cycle that composed of HWFET,LA92,Ftp75,Jal015 and NEDC driving cycles is taken as the driving cycle for simulation.Moreover,simulations under NEDC and UDDS driving cycles are taken to verify the effects of the proposed energy management strategy.Simulation results indicate that the proposed energy management strategy is effective in improving the fuel economy under different driving conditions.

关键词： plug-in hybrid electric vehicle energy management fuzzy logic SA-PSO algorithm

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Multi-objective energy management for PHEV using Pontryagin's minimum principle and particle swarm optimization online

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Science China(Information Sciences) 2021年第1期64卷 263-265页

作者： Yuying WANG Xiaohong JIAO Institute of electric Engineering Yanshan University

Dear editor,plug-in hybrid electric vehicles (PHEVs),which can be charged through an external power grid,have been regarded as one of the research areas for the developing methods to reduce petroleum demand and exhaust emissions.Energy management strategies (EMSs) are crucial for reducing the energy consumption for PHEVs because the power demands during the driving cycle are usually provided by multiple energy sources.In addition,PHEVs are often equipped with high-cost batteries,which need to be charged and discharged repeatedly.This indicates that,to achieve the economic feasibility of PHEVs,battery health cannot be ignored with respect to energy management [1].

关键词： plug-in hybrid electric vehicle energy management strategy multi-objective Pontryagin's minimum principle particle swarm optimization

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