scholarly journals Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs

2017 ◽  
Vol 9 (10) ◽  
pp. 1874 ◽  
Author(s):  
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Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Multi Objective Optimization ◽  
Energy Management Strategy ◽  
Multi Objective ◽  
Optimal Energy ◽  
Optimal Energy Management ◽  
Hybrid Ess

Optimal energy management of a fuel cell-battery-supercapacitor-powered hybrid tramway using a multi-objective approach

2019 ◽  
Vol 234 (5) ◽  
pp. 511-523 ◽  
Author(s):  
Han Zhang ◽  
Jibin Yang ◽  
Jiye Zhang ◽  
Pengyun Song ◽  
Ming Li
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Management Strategy ◽  
Operating Cost ◽  
Cell System ◽  
Energy Management Strategy ◽  
Multi Objective ◽  
Optimal Energy ◽  
Optimal Energy Management ◽  
Fuel Costs

Achieving an optimal operating cost is a challenge for the development of hybrid tramways. In the past few years, in addition to fuel costs, the lifespan of the power source is being increasingly considered as an important factor that influences the operating cost of a tramway. In this work, an optimal energy management strategy based on a multi-mode strategy and optimisation algorithm is described for a high-power fuel cell hybrid tramway. The objective of optimisation is to decrease the operating costs under the conditions of guaranteeing tramway performance. Besides the fuel costs, the replacement cost and initial investment of all power units are also considered in the cost model, which is expressed in economic terms. Using two optimisation algorithms, a multi-population genetic algorithm and an artificial fish swarm algorithm, the hybrid system's power targets for the energy management strategy were acquired using the multi-objective optimisation. The selected case study includes a low-floor light rail vehicle, and experimental validations were performed using a hardware-in-the-loop workbench. The results testify that an optimised energy management strategy can fulfil the operational requirements, reduce the daily operation costs and improve the efficiency of the fuel cell system for a hybrid tramway.

Adaptive parameter optimal energy management strategy based on multi-objective optimization for range extended electric vehicle

2021 ◽  
pp. 095440702110464
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li
Keyword(s):  
Energy Management ◽  
Control Strategy ◽  
Management Strategy ◽  
Loss Rate ◽  
Multi Objective Optimization ◽  
Energy Management Strategy ◽  
Multi Objective ◽  
Adaptive Parameter ◽  
Point Control ◽  
Optimal Energy Management

With the aim of economy improvement, emission reduction and prolonging the battery service life, an adaptive parameter optimal energy management strategy is proposed for range extended electric vehicle and a method of multi-objective optimization (MOO) is proposed. Firstly, two strategies based on different threshold parameter types, namely velocity-switch-based multi-operation-point control strategy (MCS v–b) and power-switch-based multi-operation-point control strategy (MCS p–b) are designed. Then, the oil-electric conversion loss rate, comprehensive exhaust emission, and battery capacity loss rate are selected as the optimization objectives. The barebones multi-objective particle swarm optimization is applied in MCS v–b and MCS p–b for solving the MOO problem. The simulation results show a clear conflict that three optimization objectives cannot be optimal under the same solution. And then, the individual with optimal comprehensive objective is taken as the final optimization solution to evaluate the performance of the proposed methodology. As expected, the proposed MCS p–b has a positive effect on prolonging the battery service life while ensuring high fuel economy and low emission. Experimental test results thoroughly validate the proposed approach and this result can be used to improve comprehensive performance levels.

Optimal energy management strategy for fuel cell/battery/supercapacitor vehicles using wavelet transform and equivalent consumption minimization strategy

2021 ◽  
pp. 095440702110697
Author(s):  
Pengfei Zou ◽  
Fazhan Tao ◽  
Zhumu Fu ◽  
Pengju Si ◽  
Chao Ma
Keyword(s):  
Wavelet Transform ◽  
Fuel Cell ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Low Frequency ◽  
Energy Management Strategy ◽  
Power Sources ◽  
Optimal Energy ◽  
Optimal Energy Management

In this paper, the hybrid electric vehicle is equipped with fuel cell/battery/supercapacitor as the research object, the optimal energy management strategy (EMS) is proposed by combining wavelet transform (WT) method and equivalent consumption minimization strategy (ECMS) for reducing hydrogen consumption and prolonging the lifespan of power sources. Firstly, the WT method is employed to separate power demand of vehicles into high-frequency part supplied by supercapacitor and low-frequency part allocated to fuel cell and battery, which can effectively reduce the fluctuation of fuel cell and battery to prolong their lifespan. Then, considering the low-frequency power, the optimal SOC of battery is used to design the equivalent factor of the ECMS method to improve the fuel economy. The proposed hierarchical EMS can realize a trade-off between the lifespan of power sources and fuel economy of vehicles. Finally, the effectiveness of the proposed EMS is verified by ADVISOR, and comparison results are given compared with the traditional ECMS method and ECMS combining the filter.

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