An energy matching method for battery electric vehicle and hydrogen fuel cell vehicle based on source energy consumption rate

Xiong, Hua; Liu, Huan; Zhang, Ronghui; Yu, Limin; Zong, Zhijian; Zhang, Minghui; Zhu, Li

doi:10.1016/j.ijhydene.2019.02.169

Cited by 65 publications

(25 citation statements)

References 40 publications

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“…Wang et al 57 built the physical model of supercapacitor/fuel cell/battery system and fuel cell/battery to evaluate the dynamic properties and the fuel economy in both cases. Xiong et al 58 research the way to reduce the energy consumption using a higher rate of hybrid energy proposing a Source Energy Consumption Rate (SECR) to evaluate the energy efficiency on electric vehicles. The positive results assist the efficiency of the system and the development of new ones.…”

Section: Methodsmentioning

confidence: 99%

“…Several types of classifications of energy management strategies have been suggested in the revised literature considering the criteria of taxonomy, advantages and disadvantages, the natural‐inspired algorithm used, performance obtained, etc. In the following sections, we built two classifications: the first is based on the type of algorithm, and the second is based on the goal they seek to optimize. Rule‐based strategies Fuzzy control strategy 42,76,80,82 State machine control strategy 84 Classical PI control strategy 37,43,47,48,52‐55,58,60,65,67,69,79 Power prediction 24,30,47,87,89,91 Unscented Kalman filter 61 Optimisation‐based strategies Pontryagin's minimum principle (PMP) 39,64 Quadratic programming (QPo) 38,56,86 Stochastic dynamic programming (SDP) 71,92 Multi‐mode predictive 68,90 Dynamic particle swarm optimization 28,83 Equivalent consumption minimization strategy (ECMS) 31,38,41,98 Dynamic programming (DP) 25,59,64 Genetic algorithm (GA) 40,43,76 Efficiency optimization strategy 27,29,36,57,85,93,96 Learning‐based strategies Reinforcement learning 33,62,74 Hybrid 32,46,49,63,66,70,72,73,75,77,78,81,88,95,97 …”

Section: Classification Of Strategiesmentioning

confidence: 99%

“…Compared to the problems and strategies raised in the previews 77 references [24–97, 100–102], critically commented by the authors in their work using tools as tables, diagrams, and figures, the actual problems and requests, identified from the reviewed literature from 2019 and 2020, evolved with the trends, and they are more specific and harder to archive.…”

Section: Novelty Of the Subjectmentioning

confidence: 99%

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Optimal energy management strategies for the electric vehicles compiling bibliometric maps

2021

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Summary The object of this research came from the continuing need to analyze and identify effective methods of reducing pollution and optimizing the functions of electric vehicles. So, a classic analysis of the management strategies proposed in the literature was performed to identify the main research directions that can be used to design an optimal strategy. The performed analysis was validated using different counting and representation methods in VOSviewer and Excel. VOSviewer is a program that visually presents the best research approaches for understanding and developing applications. Thus, analyzing the results obtained, it is possible to identify where the research of energy management strategies for electric vehicles is focused. For example, the most important factors for increasing the performance of a strategy are identified as related to optimization, efficiency, degradation, fuel economy, and systemic development. We identified 127 energy management strategies in the studied articles, which were analyzed and classified by multiple criteria. For example, 21.59% of the strategies have as main goal to increase the vehicles efficiency, followed by the 10% on fuel economy, 7.8% hydrogen consumption strategy, 6.29% work for performance optimization and emission reduction, and so on. So, using this tool, researchers can explore their field of research to identify challenging topics to address in the coming years.

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Section: Methodsmentioning

confidence: 99%

Section: Classification Of Strategiesmentioning

confidence: 99%

Section: Novelty Of the Subjectmentioning

confidence: 99%

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Optimal energy management strategies for the electric vehicles compiling bibliometric maps

2021

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“…Reducing hydrogen consumption by optimizing energy consumption is the subject of much research [98][99][100][101][102][103][104][105]. In addition to assessing fuel consumption, control strategies also play a role in preventing the degradation of energy storage systems, represented by batteries and the ultracapacitor [106][107][108][109]. Figure 5 describes the classifications of the energy management strategies.…”

Section: Energy Management Strategy For Fuel Cell Electric Vehiclementioning

confidence: 99%

Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies

et al. 2021

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With the development of technologies in recent decades and the imposition of international standards to reduce greenhouse gas emissions, car manufacturers have turned their attention to new technologies related to electric/hybrid vehicles and electric fuel cell vehicles. This paper focuses on electric fuel cell vehicles, which optimally combine the fuel cell system with hybrid energy storage systems, represented by batteries and ultracapacitors, to meet the dynamic power demand required by the electric motor and auxiliary systems. This paper compares the latest proposed topologies for fuel cell electric vehicles and reveals the new technologies and DC/DC converters involved to generate up-to-date information for researchers and developers interested in this specialized field. From a software point of view, the latest energy management strategies are analyzed and compared with the reference strategies, taking into account performance indicators such as energy efficiency, hydrogen consumption and degradation of the subsystems involved, which is the main challenge for car developers. The advantages and disadvantages of three types of strategies (rule-based strategies, optimization-based strategies and learning-based strategies) are discussed. Thus, future software developers can focus on new control algorithms in the area of artificial intelligence developed to meet the challenges posed by new technologies for autonomous vehicles.

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“…According to Footwear (2015), electric vehicles emerged with the goal of being an alternative to environmentally damaging impacts due to air contamination and noise emission caused by internal combustion engines. According to Xiong et al (2019) One of the obligations of electric vehicles today is to achieve lower energy use, good economy and strong practicality, all at the same time.…”

Section: Electric Vehiclesmentioning

confidence: 99%

Preliminary research about electric vehicle charging stations

Francescatto

Baierle

Habekost

et al. 2019

BJD

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With growing concern about environmental issues, there is a constant search for engineering solutions on a global scale. In this context, attention is focused on the automotive sector, which is responsible for a large part of environmentally harmful emissions. Thus, electric vehicles appear as one of the solutions to this problem. However, it is not possible to popularize these cars without a recharging structure that can meet this demand. In this context, the objective of this paper is to present studies and research carried out in the area of technical and economic feasibility focused on recharging infrastructure, in order to provide knowledge and assist future research projects in this area. Palavras-chave: Recharging Stations, Electric Vehicles, Economic Engineering. RESUMO Com crescente preocupação com questões ambientais, há uma busca constante por soluções de engenharia em escala global. Nesse contexto, a atenção está voltada para o setor automotivo, responsável por grande parte das emissões prejudiciais ao meio ambiente. Assim, os veículos elétricos aparecem como uma das soluções para esse problema. No entanto, não é possível popularizar esses carros sem uma estrutura de recarga que possa atender a essa demanda. Nesse contexto, o objetivo

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An energy matching method for battery electric vehicle and hydrogen fuel cell vehicle based on source energy consumption rate

Cited by 65 publications

References 40 publications

Optimal energy management strategies for the electric vehicles compiling bibliometric maps

Optimal energy management strategies for the electric vehicles compiling bibliometric maps

Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies

Preliminary research about electric vehicle charging stations

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