scholarly journals Comparison of Two Energy Management Strategies Considering Power System Durability for PEMFC-LIB Hybrid Logistics Vehicle

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3262
Author(s):  
Jianying Liang ◽  
Yankun Li ◽  
Wenya Jia ◽  
Weikang Lin ◽  
Tiancai Ma
Keyword(s):  
Fuel Cell ◽  
Power System ◽  
Energy Management ◽  
Fuel Economy ◽  
Lifetime Cost ◽  
Minimum Principle ◽  
Management Strategies ◽  
Energy Management Strategy ◽  
Fuzzy Control Strategy ◽  
The Cost

For commercial applications, the durability and economy of the fuel cell hybrid system have become obstacles to be overcome, which are not only affected by the performance of core materials and components, but also closely related to the energy management strategy (EMS). This paper takes the 7.9 t fuel cell logistics vehicle as the research object, and designed the EMS from two levels of qualitative and quantitative analysis, which are the composite fuzzy control strategy optimized by genetic algorithm and Pontryagin’s minimum principle (PMP) optimized by objective function, respectively. The cost function was constructed and used as the optimization objective to prolong the life of the power system as much as possible on the premise of ensuring the fuel economy. The results indicate that the optimized PMP showed a comprehensive optimal performance, the hydrogen consumption was 3.481 kg/100 km, and the cost was 13.042 $/h. The major contribution lies in that this paper presents a method to evaluate the effect of different strategies on vehicle performance including fuel economy and durability of the fuel cell and battery. The comparison between the two totally different strategies helps to find a better and effective solution to reduce the lifetime cost.

An Optimization-Oriented Supervisory Controller Design for Hybrid Fuel Cell Electrified Vehicles

2018 ◽  
Author(s):  
Kai Wu ◽  
Milos Milacic ◽  
Alhadi Albousefi ◽  
Ming Kuang ◽  
Jing Sun
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Fuel Economy ◽  
Controller Design ◽  
Minimum Principle ◽  
Test Procedure ◽  
Average Power ◽  
Energy Management Strategy ◽  
Supervisory Controller ◽  
Total Travel Time

In this paper, an optimization-oriented supervisory controller based on Pontryagin’s Minimum Principle (PMP) is established to develop an on-road energy management strategy for hybrid fuel cell vehicles. A method to estimate initial co-state value based on average power is proposed and demonstrated, which makes the offline PMP algorithm feasible for on board implementation. Furthermore, the proposed adaptive PMP (A-PMP) maintains charge-sustaining performance using readily available driving information, such as the total travel time. The A-PMP is evaluated on a high fidelity Ford fuel cell electrified vehicle powertrain with an experimentally validated fuel cell stack model. Comparing to the default baseline energy management method, the A-PMP provides better fuel economy performance. The simulation results show up to 1.1% miles per gallon gasoline equivalent (MPGe) improvement for Highway Fuel Economy Test (HWFET), 2.1% for Urban Dynamometer Driving Schedule (UDDS), and 7.0% for EPA Federal Test Procedure (FTP-75).

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.

scholarly journals Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3268
Author(s):  
Kegang Zhao ◽  
Jinghao Bei ◽  
Yanwei Liu ◽  
Zhihao Liang
Keyword(s):  
Global Optimization ◽  
Energy Management ◽  
Computational Efficiency ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Minimum Principle ◽  
Management Strategies ◽  
Energy Management Strategy ◽  
Pontryagin Minimum Principle ◽  
Component Sizing

The powertrain model of the series-parallel plug-in hybrid electric vehicles (PHEVs) is more complicated, compared with series PHEVs and parallel PHEVs. Using the traditional dynamic programming (DP) algorithm or Pontryagin minimum principle (PMP) algorithm to solve the global-optimization-based energy management strategies of the series-parallel PHEVs is not ideal, as the solution time is too long or even impossible to solve. Chief engineers of hybrid system urgently require a handy tool to quickly solve global-optimization-based energy management strategies. Therefore, this paper proposed to use the Radau pseudospectral knotting method (RPKM) to solve the global-optimization-based energy management strategy of the series-parallel PHEVs to improve computational efficiency. Simulation results showed that compared with the DP algorithm, the global-optimization-based energy management strategy based on the RPKM improves the computational efficiency by 1806 times with a relative error of only 0.12%. On this basis, a bi-level nested component-sizing method combining the genetic algorithm and RPKM was developed. By applying the global-optimization-based energy management strategy based on RPKM to the actual development, the feasibility and superiority of RPKM applied to the global-optimization-based energy management strategy of the series-parallel PHEVs were further verified.

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