Energy Management Strategy for an Electromechanical-Hydraulic Coupled Power Electric Vehicle Considering the Optimal Speed Threshold

Considering the problems of the low energy recovery efficiency and the short driving range of pure electric vehicles, a new electromechanical–hydraulic coupled power electric vehicle is proposed. First, we develop an electromechanical–hydraulic coupled power electric vehicle model and design an energy management strategy to match it. On this basis, an optimization strategy is proposed with the goal of improving the braking energy recovery efficiency and avoiding the impact of high-speed braking energy recovery on the hydraulic system. The energy recovery mode conversion is optimized for different vehicle speeds when braking. Finally, the proposed optimization strategy is verified by joint simulation. The results show that when the vehicle speed is higher than 10 m/s for energy recovery mode switching, the total recovery efficiency of the whole vehicle increases to 97.273% and the SOC of the power battery increases by 0.14%. This provides strong support for improving the driving range of electromechanical–hydraulic coupled power electric vehicles.

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Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming

Mathematical Problems in Engineering ◽

10.1155/2015/368769 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 6

Author(s):

Zeyu Chen ◽

Weiguo Liu ◽

Ying Yang ◽

Weiqiang Chen

Keyword(s):

Dynamic Programming ◽

Energy Saving ◽

Energy Management ◽

Electric Vehicles ◽

Management Strategy ◽

Hybrid Electric Vehicles ◽

Driving Cycle ◽

Energy Management Strategy ◽

Driving Range ◽

Hybrid Electric

The employed energy management strategy plays an important role in energy saving performance and exhausted emission reduction of plug-in hybrid electric vehicles (HEVs). An application of dynamic programming for optimization of power allocation is implemented in this paper with certain driving cycle and a limited driving range. Considering the DP algorithm can barely be used in real-time control because of its huge computational task and the dependence ona prioridriving cycle, several online useful control rules are established based on the offline optimization results of DP. With the above efforts, an online energy management strategy is proposed finally. The presented energy management strategy concerns the prolongation of all-electric driving range as well as the energy saving performance. A simulation study is deployed to evaluate the control performance of the proposed energy management approach. All-electric range of the plug-in HEV can be prolonged by up to 2.86% for a certain driving condition. The energy saving performance is relative to the driving distance. The presented energy management strategy brings a little higher energy cost when driving distance is short, but for a long driving distance, it can reduce the energy consumption by up to 5.77% compared to the traditional CD-CS strategy.

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