Energy Consumption Prediction and Analysis for Electric Vehicles: A Hybrid Approach

Hamza Mediouni; Amal Ezzouhri; Zakaria Charouh; Khadija El Harouri; Soumia El Hani; Mounir Ghogho

LAPSE:2023.10251

Published Article

LAPSE:2023.10251

Energy Consumption Prediction and Analysis for Electric Vehicles: A Hybrid Approach

Hamza Mediouni, Amal Ezzouhri, Zakaria Charouh, Khadija El Harouri, Soumia El Hani, Mounir Ghogho

February 27, 2023

Abstract
Range anxiety remains one of the main hurdles to the widespread adoption of electric vehicles (EVs). To mitigate this issue, accurate energy consumption prediction is required. In this study, a hybrid approach is proposed toward this objective by taking into account driving behavior, road conditions, natural environment, and additional weight. The main components of the EV were simulated using physical and equation-based models. A rich synthetic dataset illustrating different driving scenarios was then constructed. Real-world data were also collected using a city car. A machine learning model was built to relate the mechanical power to the electric power. The proposed predictive method achieved an R2 of 0.99 on test synthetic data and an R2 of 0.98 on real-world data. Furthermore, the instantaneous regenerative braking power efficiency as a function of the deceleration level was also investigated in this study.

Record ID

LAPSE:2023.10251

Keywords

hybrid approach, instantaneous regenerative braking power, range anxiety, real-world data, synthetic dataset

Subject

Energy Systems

Suggested Citation

Mediouni H, Ezzouhri A, Charouh Z, El Harouri K, El Hani S, Ghogho M. Energy Consumption Prediction and Analysis for Electric Vehicles: A Hybrid Approach. (2023). LAPSE:2023.10251

Author Affiliations

Mediouni H: Energy Optimization, Diagnosis and Control Team, Center for Research in Engineering and Health Sciences and Techniques, ENSAM, Mohammed V University, Rabat 10100, Morocco; TICLab, College of Engineering & Architecture, International University of Rabat, R [ORCID]
Ezzouhri A: TICLab, College of Engineering & Architecture, International University of Rabat, Rabat 11100, Morocco; ERSC Team, Mohammadia Engineering School, Mohammed V University, Rabat 10090, Morocco [ORCID]
Charouh Z: TICLab, College of Engineering & Architecture, International University of Rabat, Rabat 11100, Morocco; ERSC Team, Mohammadia Engineering School, Mohammed V University, Rabat 10090, Morocco [ORCID]
El Harouri K: Energy Optimization, Diagnosis and Control Team, Center for Research in Engineering and Health Sciences and Techniques, ENSAM, Mohammed V University, Rabat 10100, Morocco
El Hani S: Energy Optimization, Diagnosis and Control Team, Center for Research in Engineering and Health Sciences and Techniques, ENSAM, Mohammed V University, Rabat 10100, Morocco [ORCID]
Ghogho M: TICLab, College of Engineering & Architecture, International University of Rabat, Rabat 11100, Morocco; School of EEE, University of Leeds, Leeds LS2 9JT, UK [ORCID]

Journal Name

Energies

Volume

15

Issue

17

First Page

6490

Year

2022

Publication Date

2022-09-05