scholarly journals A Firefly Algorithm Optimization-Based Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Light Rail Vehicle

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2665 ◽  
Author(s):  
Han Zhang ◽  
Jibin Yang ◽  
Jiye Zhang ◽  
Pengyun Song ◽  
Xiaohui Xu

To coordinate multiple power sources properly, this paper presents an optimal control strategy for a fuel cell/battery/supercapacitor light rail vehicle. The proposed strategy, which uses the firefly algorithm to optimize the equivalent consumption minimization strategy, improves the drawback that the conventional equivalent consumption minimization strategy takes insufficient account of the global performance for the vehicle. Moreover, the strategy considers the difference between the two sets of optimized variables. The optimization objective is to minimize the daily operating cost of the vehicle, which includes the total fuel consumption, initial investment, and cycling costs of power sources. The selected case study is a 100% low-floor light rail vehicle. The advantages of the proposed strategy are investigated by comparison with the operating mode control, firefly algorithm-based operating mode control, and equivalent consumption minimization strategy. In contrast to other methods, the proposed strategy shows cost reductions of up to 39.62% (from operating mode control), 18.28% (from firefly algorithm-based operating mode control), and 13.81% (from equivalent consumption minimization strategy). In addition, the proposed strategy can reduce fuel consumption and increase the efficiency of the fuel cell system.

2021 ◽  
Vol 30 (3) ◽  
pp. 121-130
Author(s):  
Awais SHAH ◽  
Deqing HUANG ◽  
Tianpeng HUANG ◽  
Na QIN

Author(s):  
Ling-Kun Chen ◽  
Peng Liu ◽  
Li-Ming Zhu ◽  
Jing-Bo Ding ◽  
Yu-Lin Feng ◽  
...  

Near-fault (NF) earthquakes cause severe bridge damage, particularly urban bridges subjected to light rail transit (LRT), which could affect the safety of the light rail transit vehicle (“light rail vehicle” or “LRV” for short). Now when a variety of studies on the fault fracture effect on the working protection of LRVs are available for the study of cars subjected to far-reaching soil motion (FFGMs), further examination is appropriate. For the first time, this paper introduced the LRV derailment mechanism caused by pulse-type near-fault ground motions (NFGMs), suggesting the concept of pulse derailment. The effects of near-fault ground motions (NFGMs) are included in an available numerical process developed for the LRV analysis of the VBI system. A simplified iterative algorithm is proposed to assess the stability and nonlinear seismic response of an LRV-reinforced concrete (RC) viaduct (LRVBRCV) system to a long-period NFGMs using the dynamic substructure method (DSM). Furthermore, a computer simulation software was developed to compute the nonlinear seismic responses of the VBI system to pulse-type NFGMs, non-pulse-type NFGMs, and FFGMs named Dynamic Interaction Analysis for Light-Rail-Vehicle Bridge System (DIALRVBS). The nonlinear bridge seismic reaction determines the impact of pulses on lateral peak earth acceleration (Ap) and lateral peak land (Vp) ratios. The analysis results quantify the effects of pulse-type NFGMs seismic responses on the LRV operations' safety. In contrast with the pulse-type non-pulse NFGMs and FFGMs, this article's research shows that pulse-type NFGM derail trains primarily via the transverse velocity pulse effect. Hence, this study's results and the proposed method can improve the LRT bridges' seismic designs.


Author(s):  
Tao Deng ◽  
Ke Zhao ◽  
Haoyuan Yu

In the process of sufficiently considering fuel economy of plug-in hybrid electric vehicle (PHEV), the working time of engine will be reduced accordingly. The increased frequency that the three-way catalytic converter (TWCC) works in abnormal operating temperature will lead to the increasing of emissions. This paper proposes the equivalent consumption minimization strategy (ECMS) to ensure the catalyst temperature of PHEV can work in highly efficient areas, and the influence of catalyst temperature on fuel economy and emissions is considered. The simulation results show that the fixed equivalent factor of ECMS has great limitations for the underutilized battery power and the poor fuel economy. In order to further reduce fuel consumption and keep the emission unchanged, an equivalent factor map based on initial state of charge (SOC) and vehicle mileage is established by the genetic algorithm. Furthermore, an Adaptive changing equivalent factor is achieved by using the following strategy of SOC trajectory. Ultimately, adaptive equivalent consumption minimization strategy (A-ECMS) considering catalyst temperature is proposed. The simulation results show that compared with ordinary ECMS, HC, CO, and NOX are reduced by 14.6%, 20.3%, and 25.8%, respectively, which effectively reduces emissions. But the fuel consumption is increased by only 2.3%. To show that the proposed method can be used in actual driving conditions, it is tested on the World Light Vehicle Test Procedure (WLTC).


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