Review on Braking Energy Management in Electric Vehicles
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Shu-zhi Gao & Jing Yang & Jie-sheng Wang, 2014. "D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-13, April.
- Jakov Topić & Branimir Škugor & Joško Deur, 2019. "Neural Network-Based Modeling of Electric Vehicle Energy Demand and All Electric Range," Energies, MDPI, vol. 12(7), pages 1-20, April.
- Aritra Ghosh, 2020. "Possibilities and Challenges for the Inclusion of the Electric Vehicle (EV) to Reduce the Carbon Footprint in the Transport Sector: A Review," Energies, MDPI, vol. 13(10), pages 1-22, May.
- Guoqing Xu & Weimin Li & Kun Xu & Zhibin Song, 2011. "An Intelligent Regenerative Braking Strategy for Electric Vehicles," Energies, MDPI, vol. 4(9), pages 1-17, September.
- Boyi Xiao & Huazhong Lu & Hailin Wang & Jiageng Ruan & Nong Zhang, 2017. "Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis," Energies, MDPI, vol. 10(11), pages 1-19, November.
- Valery Vodovozov & Andrei Aksjonov & Eduard Petlenkov & Zoja Raud, 2021. "Neural Network-Based Model Reference Control of Braking Electric Vehicles," Energies, MDPI, vol. 14(9), pages 1-22, April.
- Jingang Guo & Xiaoping Jian & Guangyu Lin, 2014. "Performance Evaluation of an Anti-Lock Braking System for Electric Vehicles with a Fuzzy Sliding Mode Controller," Energies, MDPI, vol. 7(10), pages 1-18, October.
- Kanghyun Nam & Yoichi Hori & Choonyoung Lee, 2015. "Wheel Slip Control for Improving Traction-Ability and Energy Efficiency of a Personal Electric Vehicle," Energies, MDPI, vol. 8(7), pages 1-21, July.
- He, Hongwen & Wang, Chen & Jia, Hui & Cui, Xing, 2020. "An intelligent braking system composed single-pedal and multi-objective optimization neural network braking control strategies for electric vehicle," Applied Energy, Elsevier, vol. 259(C).
- Lee, Henry & Clark, Alex, 2018. "Charging the Future: Challenges and Opportunities for Electric Vehicle Adoption," Working Paper Series rwp18-026, Harvard University, John F. Kennedy School of Government.
- Yang Yang & Chang Luo & Pengxi Li, 2017. "Regenerative Braking Control Strategy of Electric-Hydraulic Hybrid (EHH) Vehicle," Energies, MDPI, vol. 10(7), pages 1-18, July.
- Sabrine Slama & Ayachi Errachdi & Mohamed Benrejeb, 2019. "Neural Adaptive PID and Neural Indirect Adaptive Control Switch Controller for Nonlinear MIMO Systems," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-11, August.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Khaled Itani & Alexandre De Bernardinis, 2022. "Electrothermal Multicriteria Comparative Analysis of Two Competitive Powertrains Applied to a Two Front Wheel Driven Electric Vehicle during Extreme Regenerative Braking Operations," Energies, MDPI, vol. 15(22), pages 1-27, November.
- Gianfranco Rizzo & Francesco Antonio Tiano & Valerio Mariani & Matteo Marino, 2021. "Optimal Modulation of Regenerative Braking in Through-The-Road Hybridized Vehicles," Energies, MDPI, vol. 14(20), pages 1-15, October.
- Giulia Sandrini & Daniel Chindamo & Marco Gadola, 2022. "Regenerative Braking Logic That Maximizes Energy Recovery Ensuring the Vehicle Stability," Energies, MDPI, vol. 15(16), pages 1-43, August.
- Md. Sazal Miah & Molla Shahadat Hossain Lipu & Sheikh Tanzim Meraj & Kamrul Hasan & Shaheer Ansari & Taskin Jamal & Hasan Masrur & Rajvikram Madurai Elavarasan & Aini Hussain, 2021. "Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
- Yang, Chao & Sun, Tonglin & Wang, Weida & Li, Ying & Zhang, Yuhang & Zha, Mingjun, 2024. "Regenerative braking system development and perspectives for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
- Jacek Caban & Jan Vrabel & Dorota Górnicka & Radosław Nowak & Maciej Jankiewicz & Jonas Matijošius & Marek Palka, 2023. "Overview of Energy Harvesting Technologies Used in Road Vehicles," Energies, MDPI, vol. 16(9), pages 1-32, April.
- Deping Wang & Changyang Guan & Junnian Wang & Haisheng Wang & Zhenhao Zhang & Dachang Guo & Fang Yang, 2023. "Review of Energy-Saving Technologies for Electric Vehicles, from the Perspective of Driving Energy Management," Sustainability, MDPI, vol. 15(9), pages 1-17, May.
- Agnieszka Dudziak & Jacek Caban & Ondrej Stopka & Monika Stoma & Marie Sejkorová & Mária Stopková, 2023. "Vehicle Market Analysis of Drivers’ Preferences in Terms of the Propulsion Systems: The Czech Case Study," Energies, MDPI, vol. 16(5), pages 1-20, March.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Yang, Chao & Sun, Tonglin & Wang, Weida & Li, Ying & Zhang, Yuhang & Zha, Mingjun, 2024. "Regenerative braking system development and perspectives for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
- Changran He & Guoye Wang & Zhangpeng Gong & Zhichao Xing & Dongxin Xu, 2018. "A Control Algorithm for the Novel Regenerative–Mechanical Coupled Brake System with by-Wire Based on Multidisciplinary Design Optimization for an Electric Vehicle," Energies, MDPI, vol. 11(9), pages 1-18, September.
- Emilia M. Szumska & Rafał Jurecki, 2022. "The Analysis of Energy Recovered during the Braking of an Electric Vehicle in Different Driving Conditions," Energies, MDPI, vol. 15(24), pages 1-16, December.
- Valery Vodovozov & Andrei Aksjonov & Eduard Petlenkov & Zoja Raud, 2021. "Neural Network-Based Model Reference Control of Braking Electric Vehicles," Energies, MDPI, vol. 14(9), pages 1-22, April.
- Zhou, Xiaochuan & Wu, Gang & Wang, Chunyan & Zhang, Ruijun & Shi, Shuaipeng & Zhao, Wanzhong, 2024. "Cooperative optimization of energy recovery and braking feel based on vehicle speed prediction under downshifting conditions," Energy, Elsevier, vol. 301(C).
- He, Qiang & Yang, Yang & Luo, Chang & Zhai, Jun & Luo, Ronghua & Fu, Chunyun, 2022. "Energy recovery strategy optimization of dual-motor drive electric vehicle based on braking safety and efficient recovery," Energy, Elsevier, vol. 248(C).
- Yang, Jian & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Zhao, Qinghai & Meng, Zewen, 2021. "Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 233(C).
- Timo Busch & Michael L. Barnett & Roger Leonard Burritt & Benjamin W. Cashore & R. Edward Freeman & Irene Henriques & Bryan W. Husted & Rajat Panwar & Jonatan Pinkse & Stefan Schaltegger & Jeff York, 2024. "Moving beyond “the” business case: How to make corporate sustainability work," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 776-787, February.
- Peter Girovský & Jaroslava Žilková & Ján Kaňuch, 2020. "Optimization of Vehicle Braking Distance Using a Fuzzy Controller," Energies, MDPI, vol. 13(11), pages 1-15, June.
- Jiaming Zhou & Chunxiao Feng & Qingqing Su & Shangfeng Jiang & Zhixian Fan & Jiageng Ruan & Shikai Sun & Leli Hu, 2022. "The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
- Liang Zhang & Shunli Wang & Daniel-Ioan Stroe & Chuanyun Zou & Carlos Fernandez & Chunmei Yu, 2020. "An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries," Energies, MDPI, vol. 13(8), pages 1-12, April.
- Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
- Gull, Muhammad Shuzub & Khalid, Muhammad & Arshad, Naveed, 2024. "Multi-objective optimization of battery swapping station to power up mobile and stationary loads," Applied Energy, Elsevier, vol. 374(C).
- Duo Zhang & Guohai Liu & Wenxiang Zhao & Penghu Miao & Yan Jiang & Huawei Zhou, 2014. "A Neural Network Combined Inverse Controller for a Two-Rear-Wheel Independently Driven Electric Vehicle," Energies, MDPI, vol. 7(7), pages 1-15, July.
- Jingang Guo & Xiaoping Jian & Guangyu Lin, 2014. "Performance Evaluation of an Anti-Lock Braking System for Electric Vehicles with a Fuzzy Sliding Mode Controller," Energies, MDPI, vol. 7(10), pages 1-18, October.
- Jacek Caban & Jan Vrabel & Dorota Górnicka & Radosław Nowak & Maciej Jankiewicz & Jonas Matijošius & Marek Palka, 2023. "Overview of Energy Harvesting Technologies Used in Road Vehicles," Energies, MDPI, vol. 16(9), pages 1-32, April.
- Mauro Zucca & Vincenzo Cirimele & Jorge Bruna & Davide Signorino & Erika Laporta & Jacopo Colussi & Miguel Angel Alonso Tejedor & Federico Fissore & Umberto Pogliano, 2021. "Assessment of the Overall Efficiency in WPT Stations for Electric Vehicles," Sustainability, MDPI, vol. 13(5), pages 1-19, February.
- Anam Nadeem & Mosè Rossi & Erica Corradi & Lingkang Jin & Gabriele Comodi & Nadeem Ahmed Sheikh, 2022. "Energy-Environmental Planning of Electric Vehicles (EVs): A Case Study of the National Energy System of Pakistan," Energies, MDPI, vol. 15(9), pages 1-19, April.
- Jelena Loncarski & Vito Giuseppe Monopoli & Giuseppe Leonardo Cascella & Francesco Cupertino, 2020. "SiC-MOSFET and Si-IGBT-Based dc-dc Interleaved Converters for EV Chargers: Approach for Efficiency Comparison with Minimum Switching Losses Based on Complete Parasitic Modeling," Energies, MDPI, vol. 13(17), pages 1-20, September.
- Jiangbo Wang & Kai Liu & Toshiyuki Yamamoto, 2017. "Improving Electricity Consumption Estimation for Electric Vehicles Based on Sparse GPS Observations," Energies, MDPI, vol. 10(1), pages 1-12, January.
More about this item
Keywords
electric vehicles; energy efficiency; regenerative braking; intelligent controllers; fuzzy logic; neural network;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:15:p:4477-:d:600645. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.