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Hybrid Energy System in Electric Vehicles

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 8867

Special Issue Editors


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Guest Editor
Intelligent Machinery Research Institute, Beijing University of Technology, Beijing, China
Interests: powertrain topology; design and optimization of electric vehicles; energy storage system configuration; sizing and energy management strategy optimization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
Interests: automated and connected vehicles; vehicle dynamics and control; battery management techniques
Special Issues, Collections and Topics in MDPI journals
Chair for Electrochemical Energy Conversion and Storage Systems, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, 52066 Aachen, Germany
Interests: batteries; machine learning; battery management systems; energy management systems; electrochemical modeling

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Guest Editor
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
Interests: data-driven and electrochemical mechanism modeling; parameter identification; state estimation, health diagnosis, and second-life utilization of lithium-ion batteries
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The market share of the global electric vehicle (EV) has taken a tremendous leap forward in the past decade. Considering the commitment to achieve carbon neutrality and carbon zero worldwide, fiscal incentives or related supporting policies, e.g., registration priority, will be provided or extended to buffer EV purchases from the downturn in car markets. Therefore, it is sensible to expect an exponential acceleration in EV registration around the world in the following years.

On the other hand, although EVs are gradually becoming more competitive in some countries in terms of a total cost of ownership basis, the driving range degradation caused by battery aging; the battery’s long charging time; and the cost, production, and environmental protection issues caused by strong demand for electrochemical cell-based batteries. Hybrid energy storage systems (HESS) are one of the more promising solutions that can be implemented to address these concerns. Battery–supercapacitors, battery–hydrogen fuel cells, and other battery–high power/energy density chemistries are proposed to improve EV performance in terms of driving range, charging time, battery capacity degradation by aging, and so on.

This Special Issue is expected to provide a platform through which the latest developments on HESS for electric vehicles can be shared. Researchers in this field are encouraged to contribute their scientific innovations, application-of-use cases, state-of-the-art reviews, and benchmarking studies. The following topics are welcomed, but submissions are not limited to the list of topics below:

  • Design, system engineering, and field applications of HESS for EV;
  • Modeling, simulation, testing, and verification for renewable energy sources in HESS;
  • Coordination sizing and energy management of HESS;
  • Power conversion electronics for renewable energy sources;
  • Power electronic architectures for HESS;
  • Aging mechanisms of power converters and energy storage devices;
  • Online estimation of state-of-charge, state-of-health, and state-of-power;
  • Aging modeling and lifetime prediction;
  • Power electronic architectures for HESS;
  • Solid-state battery technology;
  • Hydrogen fuel cell technology;
  • Supercapacitor technology;
  • Machine learning, big data, and cloud computing in HESS applications;
  • Real-time energy management and predictive optimization methodologies;
  • Monitoring and predictive maintenance of HESS;
  • Life cycle analysis, including re-use of HESS in second-life applications.

Prof. Dr. Jiageng Ruan
Prof. Dr. Lei Zhang
Dr. Weihan Li
Dr. Zhongwei Deng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hybrid energy storage systems
  • batteries
  • supercapacitor
  • fuel cell
  • energy management strategy
  • health monitoring and estimation
  • machine learning

Published Papers (5 papers)

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Research

21 pages, 3158 KiB  
Article
Improving Sustainability in Urban and Road Transportation: Dual Battery Block and Fuel Cell Hybrid Power System for Electric Vehicles
by Carlos Armenta-Déu
Sustainability 2024, 16(5), 2110; https://doi.org/10.3390/su16052110 - 03 Mar 2024
Viewed by 945
Abstract
This work aims to study and analyze sustainability improvement in urban and road transportation by using a hybrid power system for electric vehicles consisting of a dual low- and high-rate operation lithium battery block and a fuel cell. The proposed power system reduces [...] Read more.
This work aims to study and analyze sustainability improvement in urban and road transportation by using a hybrid power system for electric vehicles consisting of a dual low- and high-rate operation lithium battery block and a fuel cell. The proposed power system reduces the energy consumption in electric vehicles, thus helping to enhance a sustainable process of environmental urban pollution and reducing or eliminating fossil fuel dependence, enhancing global sustainability. In this configuration, the high-rate lithium battery powers the electric vehicle in high-power-demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads, and the fuel cell supplies energy in intermediate-power-demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency, since every power unit operates optimally, depending on the driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cells shows an efficiency improvement of 31.4% for the hybrid dual-battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study is based on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell, and high-rate lithium battery produces a 29% power gain. Full article
(This article belongs to the Special Issue Hybrid Energy System in Electric Vehicles)
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16 pages, 6697 KiB  
Article
A Quantitative Study on Driving Behavior Economy Based on Big Data from the Pure Electric Bus
by Hongli Liu, Weiguo Yun, Bin Li, Mengling Dai and Yangyuhang Wang
Sustainability 2023, 15(10), 8033; https://doi.org/10.3390/su15108033 - 15 May 2023
Viewed by 1023
Abstract
In order to help improve the economy, energy savings and emission reductions of pure electric buses, based on the driving data, a new driving cycle construction method is proposed. Through the dividing of short trips and the calculation of characteristic parameter values, two [...] Read more.
In order to help improve the economy, energy savings and emission reductions of pure electric buses, based on the driving data, a new driving cycle construction method is proposed. Through the dividing of short trips and the calculation of characteristic parameter values, two typical driving conditions (weekday driving condition and weekend driving condition) are constructed via principal components analysis and the k-means clustering method, and both have a high degree of compatibility with the actual conditions. Based on the two typical driving conditions, the CRITIC (Criteria Importance Through Intercriteria Correlation) method and the quantitative analysis are used to establish a quantitative evaluation model to score the economy of the driver’s driving behavior. The result shows that the weekend working condition with the better traffic environment promotes the generation of aggressive driving behavior and increases the random fluctuation seen in the driver’s driving process: for the weekend driving condition, the proportion of low economic efficiency is about 4.5 times bigger than the proportion on weekdays, and the former’s fluctuation range for the driving behavior score is 37% higher than that of the latter, meaning that the overall economy of the pure electric bus is much worse on weekends. Full article
(This article belongs to the Special Issue Hybrid Energy System in Electric Vehicles)
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13 pages, 4408 KiB  
Article
An Investigation of Opportunity Charging with Hybrid Energy Storage System on Electric Bus with Two-Speed Transmission
by Ying Yang, Zhenpo Wang, Shuo Wang and Ni Lin
Sustainability 2022, 14(19), 11918; https://doi.org/10.3390/su141911918 - 21 Sep 2022
Cited by 1 | Viewed by 1488
Abstract
As one of the most popular and important forms of massive transit, the public bus contributes to a healthier environment compared to private vehicles. Through the electrification of the public bus, energy consumption, carbon emission, and air pollution can be significantly reduced. However, [...] Read more.
As one of the most popular and important forms of massive transit, the public bus contributes to a healthier environment compared to private vehicles. Through the electrification of the public bus, energy consumption, carbon emission, and air pollution can be significantly reduced. However, the limited driving range and high battery replacement cost put significant barriers to its large-scale commercialization. Thanks to the development of wireless charging technology and opportunity charging strategy, the driving range can be improved. However, the battery has to suffer additional impulse current generated by opportunity wireless charging. In this paper, a hybrid energy storage system (HESS) that combines battery and supercapacitor and related energy control strategy is proposed to smoothen the impulse current and extend the battery lifespan. A comprehensive investigation of the combined impacts of the opportunity charging and HESS is carried out in terms of driving range extension and battery lifespan improvement. The detailed HESS model and powertrain model are built. A global optimizing method, dynamic programming, is adopted as the energy management strategy under the Chinese heavy-duty commercial vehicle test cycle-bus (CHTC-B). A battery degradation model is employed to evaluate its health with 60 kW wireless charging. The results demonstrate that the proposed energy control strategy for HESS could improve battery health and extend bus driving range concurrently via opportunity charging. Full article
(This article belongs to the Special Issue Hybrid Energy System in Electric Vehicles)
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16 pages, 4919 KiB  
Article
Powertrain Design and Energy Management Strategy Optimization for a Fuel Cell Electric Intercity Coach in an Extremely Cold Mountain Area
by Zhaowen Liang, Kai Liu, Jinjin Huang, Enfei Zhou, Chao Wang, Hui Wang, Qiong Huang and Zhenpo Wang
Sustainability 2022, 14(18), 11253; https://doi.org/10.3390/su141811253 - 08 Sep 2022
Viewed by 1366
Abstract
Facing the challenge that the single-motor electric drive powertrain cannot meet the continuous uphill requirements in the cold mountainous area of the 2022 Beijing Winter Olympics, the manuscript adopted a dual-motor coupling technology. Then, according to the operating characteristics and performance indicators of [...] Read more.
Facing the challenge that the single-motor electric drive powertrain cannot meet the continuous uphill requirements in the cold mountainous area of the 2022 Beijing Winter Olympics, the manuscript adopted a dual-motor coupling technology. Then, according to the operating characteristics and performance indicators of the fuel cell (FC)–traction battery hybrid power system, the structure design and parameter matching of the vehicle power system architecture were carried out to improve the vehicle’s dynamic performance. Furthermore, considering the extremely cold conditions in the Winter Olympics competition area and the poor low-temperature tolerance of core components of fuel cell electric vehicles (FCEV) under extremely cold conditions, such as the reduced capacity and service life of traction batteries caused by the rapid deterioration of charging and discharging characteristics, the manuscript proposed a fuzzy logic control-based energy management strategy (EMS) optimization method for the proton exchange membrane fuel cell (PEMFC), to reduce the power fluctuation, hydrogen consumption and battery charging/discharging times, and at the same time, to ensure the hybrid power system meets the varying demand under different conditions. In addition, the performance of the proposed approach was investigated and validated in an intercity coach in real-world driving conditions. The experimental results show that the proposed powertrain with an optimal control strategy successfully alleviated the fluctuation of vehicle power demand, reduced the battery charging/discharging times of traction battery, and improved the energy efficiency by 20.7%. The research results of this manuscript are of great significance for the future promotion and application of fuel cell electric coaches in all climate environments, especially in an extremely cold mountain area. Full article
(This article belongs to the Special Issue Hybrid Energy System in Electric Vehicles)
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21 pages, 39640 KiB  
Article
Early Prognostics of Lithium-Ion Battery Pack Health
by Jiwei Wang, Zhongwei Deng, Kaile Peng, Xinchen Deng, Lijun Xu, Guoqing Guan and Abuliti Abudula
Sustainability 2022, 14(4), 2313; https://doi.org/10.3390/su14042313 - 17 Feb 2022
Cited by 3 | Viewed by 2168
Abstract
Accurate health prognostics of lithium-ion battery packs play a crucial role in timely maintenance and avoiding potential safety accidents in energy storage. To rapidly evaluate the health of newly developed battery packs, a method for predicting the future health of the battery pack [...] Read more.
Accurate health prognostics of lithium-ion battery packs play a crucial role in timely maintenance and avoiding potential safety accidents in energy storage. To rapidly evaluate the health of newly developed battery packs, a method for predicting the future health of the battery pack using the aging data of the battery cells for their entire lifecycles and with the early cycling data of the battery pack is proposed. Firstly, health indicators (HIs) are extracted from the experimental data, and high correlations between the extracted HIs and the capacity are verified by the Pearson correlation analysis method. To predict the future health of the battery pack based on the HIs, degradation models of HIs are constructed by using an exponential function, long short-term memory network, and their weighted fusion. The future HIs of the battery pack are predicted according to the fusion degradation model. Then, based on the Gaussian process regression algorithm and battery pack data, a data-driven model is constructed to predict the health of the battery pack. Finally, the proposed method is validated with a series-connected battery pack with fifteen 100 Ah lithium iron phosphate battery cells. The mean absolute error and root mean square error of the health prediction of the battery pack are 7.17% and 7.81%, respectively, indicating that the proposed method has satisfactory accuracy. Full article
(This article belongs to the Special Issue Hybrid Energy System in Electric Vehicles)
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