IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i11p4283-d1154091.html
   My bibliography  Save this article

An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements

Author

Listed:
  • Yossi Hadad

    (Department of Industrial Engineering and Management, SCE—Shamoon College of Engineering, Beer-Shvea 8410802, Israel)

  • Baruch Keren

    (Department of Industrial Engineering and Management, SCE—Shamoon College of Engineering, Beer-Shvea 8410802, Israel)

  • Dima Alberg

    (Department of Industrial Engineering and Management, SCE—Shamoon College of Engineering, Beer-Shvea 8410802, Israel)

Abstract

Electric vehicles (EVs) have become popular in the last decade because of their advantages compared to conventional vehicles. The market offers dozens of EV models in a large range of prices, performances, and specifications. This paper presents an expert system we developed to support sellers and customers in choosing an EV that matches the customers’ specifications. The system enables ranking-specific EVs according to the customers’ specifications and counting the number of mismatches. The paper analyzes a database of 53 different EVs, each with 22 different characteristics, enabling customers to choose the EV that best suits their most important specifications. Based on the customer’s requirements and the principle of fuzzy sets, the system assigns a matching value to each criterion. These matching values are the input matrix for the TOPSIS procedure that ranks all the EVs according to their matching scores for a specific customer. The applicability of the proposed method is demonstrated for one customer with specific preferred EV requirements. A Python code of this method is also available herein.

Suggested Citation

  • Yossi Hadad & Baruch Keren & Dima Alberg, 2023. "An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements," Energies, MDPI, vol. 16(11), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4283-:d:1154091
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/11/4283/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/11/4283/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    2. Wu, Yang Andrew & Ng, Artie W. & Yu, Zichao & Huang, Jie & Meng, Ke & Dong, Z.Y., 2021. "A review of evolutionary policy incentives for sustainable development of electric vehicles in China: Strategic implications," Energy Policy, Elsevier, vol. 148(PB).
    3. Katarzyna Sobiech-Grabka & Anna Stankowska & Krzysztof Jerzak, 2022. "Determinants of Electric Cars Purchase Intention in Poland: Personal Attitudes v. Economic Arguments," Energies, MDPI, vol. 15(9), pages 1-26, April.
    4. Wang, Endong, 2015. "Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach," Applied Energy, Elsevier, vol. 146(C), pages 92-103.
    5. Charles Lincoln Kenji Yamamura & Harmi Takiya & Cláudia Aparecida Soares Machado & José Carlos Curvelo Santana & José Alberto Quintanilha & Fernando Tobal Berssaneti, 2022. "Electric Cars in Brazil: An Analysis of Core Green Technologies and the Transition Process," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    6. Li, Zhenhe & Khajepour, Amir & Song, Jinchun, 2019. "A comprehensive review of the key technologies for pure electric vehicles," Energy, Elsevier, vol. 182(C), pages 824-839.
    7. Paweł Ziemba, 2020. "Multi-Criteria Stochastic Selection of Electric Vehicles for the Sustainable Development of Local Government and State Administration Units in Poland," Energies, MDPI, vol. 13(23), pages 1-19, November.
    8. Das, Ridoy & Wang, Yue & Putrus, Ghanim & Kotter, Richard & Marzband, Mousa & Herteleer, Bert & Warmerdam, Jos, 2020. "Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services," Applied Energy, Elsevier, vol. 257(C).
    9. Adam Deptuła & Andrzej Augustynowicz & Michał Stosiak & Krzysztof Towarnicki & Mykola Karpenko, 2022. "The Concept of Using an Expert System and Multi-Valued Logic Trees to Assess the Energy Consumption of an Electric Car in Selected Driving Cycles," Energies, MDPI, vol. 15(13), pages 1-24, June.
    10. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    11. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    12. Vasileios Boglou & Christos-Spyridon Karavas & Konstantinos Arvanitis & Athanasios Karlis, 2020. "A Fuzzy Energy Management Strategy for the Coordination of Electric Vehicle Charging in Low Voltage Distribution Grids," Energies, MDPI, vol. 13(14), pages 1-34, July.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Fumin Deng & Yanjie Li & Huirong Lin & Jinrui Miao & Xuedong Liang, 2020. "A BWM-TOPSIS Hazardous Waste Inventory Safety Risk Evaluation," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    2. Peipei You & Sen Guo & Haoran Zhao & Huiru Zhao, 2017. "Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    3. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    4. Junnan Wu & Xin Liu & Dianqi Pan & Yichen Zhang & Jiquan Zhang & Kai Ke, 2023. "Research on Safety Evaluation of Municipal Sewage Treatment Plant Based on Improved Best-Worst Method and Fuzzy Comprehensive Method," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    5. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    6. Pushparenu Bhattacharjee & Syed Abou Iltaf Hussain & V. Dey & U. K. Mandal, 2023. "Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1778-1798, October.
    7. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    8. Yuanxin Liu & FengYun Li & Yi Wang & Xinhua Yu & Jiahai Yuan & Yuwei Wang, 2018. "Assessing the Environmental Impact Caused by Power Grid Projects in High Altitude Areas Based on BWM and Vague Sets Techniques," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    9. Ravindra Singh Saluja & Varinder Singh, 2023. "Attribute-based characterization, coding, and selection of joining processes using a novel MADM approach," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 616-655, June.
    10. Ghadimi, Pezhman & Donnelly, Oisin & Sar, Kubra & Wang, Chao & Azadnia, Amir Hossein, 2022. "The successful implementation of industry 4.0 in manufacturing: An analysis and prioritization of risks in Irish industry," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    11. Mostafayi Darmian, Sobhan & Tavana, Madjid & Ribeiro-Navarrete, Samuel, 2024. "An investment evaluation and incentive allocation model for public-private partnerships in renewable energy development projects," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    12. Liu, Xiao & Li, Ming-Yang, 2024. "Sustainable service product design method: Focus on customer demands and triple bottom line," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    13. Junli Zhang & Guoteng Wang & Zheng Xu & Zheren Zhang, 2022. "A Comprehensive Evaluation Method and Strengthening Measures for AC/DC Hybrid Power Grids," Energies, MDPI, vol. 15(12), pages 1-20, June.
    14. Hamzeh Soltanali & Mehdi Khojastehpour & Siamak Kheybari, 2023. "Evaluating the critical success factors for maintenance management in agro-industries using multi-criteria decision-making techniques," Operations Management Research, Springer, vol. 16(2), pages 949-968, June.
    15. Corrente, Salvatore & Greco, Salvatore & Rezaei, Jafar, 2024. "Better decisions with less cognitive load: The Parsimonious BWM," Omega, Elsevier, vol. 126(C).
    16. Vieira, Fabiana C. & Ferreira, Fernando A.F. & Govindan, Kannan & Ferreira, Neuza C.M.Q.F. & Banaitis, Audrius, 2022. "Measuring urban digitalization using cognitive mapping and the best worst method (BWM)," Technology in Society, Elsevier, vol. 71(C).
    17. Besharati Fard, Moein & Moradian, Parisa & Emarati, Mohammadreza & Ebadi, Mehdi & Gholamzadeh Chofreh, Abdoulmohammad & Klemeŝ, Jiří Jaromír, 2022. "Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    18. Mei, Mei & Chen, Zhihua, 2021. "Evaluation and selection of sustainable hydrogen production technology with hybrid uncertain sustainability indicators based on rough-fuzzy BWM-DEA," Renewable Energy, Elsevier, vol. 165(P1), pages 716-730.
    19. Javid Nafari & Alireza Arab & Sina Ghaffari, 2017. "Through the Looking Glass: Analysis of Factors Influencing Iranian Student’s Study Abroad Motivations and Destination Choice," SAGE Open, , vol. 7(2), pages 21582440177, June.
    20. Shabnam Mehrnoor & Maryam Robati & Mir Masoud Kheirkhah Zarkesh & Forough Farsad & Shahram Baikpour, 2023. "Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(3), pages 1997-2030, February.

    Corrections

    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:16:y:2023:i:11:p:4283-:d:1154091. 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.