Vehicle Velocity Prediction and Energy Management Strategy Part 2: Integration of Machine Learning Vehicle Velocity Prediction with Optimal Energy Management to Improve Fuel Economy

2019 ◽  
Author(s):  
Tushar D. Gaikwad ◽  
Zachary D. Asher ◽  
Kuan Liu ◽  
Mike Huang ◽  
Ilya Kolmanovsky
Keyword(s):  
Machine Learning ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Improve Fuel Economy ◽  
Optimal Energy ◽  
Vehicle Velocity ◽  
Velocity Prediction ◽  
Optimal Energy Management

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.

Optimal energy management strategy for a plug-in hybrid electric commercial vehicle based on velocity prediction

Energy ◽  
2018 ◽  
Vol 155 ◽  
pp. 838-852 ◽  
Author(s):  
Peihong Shen ◽  
Zhiguo Zhao ◽  
Xiaowen Zhan ◽  
Jingwei Li ◽  
Qiuyi Guo
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Commercial Vehicle ◽  
Energy Management Strategy ◽  
Optimal Energy ◽  
Velocity Prediction ◽  
Optimal Energy Management ◽  
Hybrid Electric

Optimal energy management strategy for battery powered electric vehicles

2014 ◽  
Vol 134 ◽  
pp. 332-341 ◽  
Author(s):  
Jiaqi Xi ◽  
Mian Li ◽  
Min Xu
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Optimal Energy ◽  
Optimal Energy Management

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.

scholarly journals Design of an instantaneous optimal energy management strategy for a dual-axis-parallel plug-in hybrid electric vehicle

2017 ◽  
Vol 139 ◽  
pp. 00034
Author(s):  
Yan Zhengjun ◽  
Wang Weida ◽  
Li Hongcai ◽  
Han Lijin ◽  
Lv Yong ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Energy Management Strategy ◽  
Optimal Energy ◽  
Axis Parallel ◽  
Optimal Energy Management ◽  
Hybrid Electric
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