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Analysis of Energy Consumption and Energy Efficiency of Electric Vehicles

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: 27 January 2026 | Viewed by 24879

Special Issue Editor


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Guest Editor
Department of Automotive Engineering and Transport, Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, 25-314 Kielce, Poland
Interests: electric vehicle; hybrid vehicle; driver behavior; life cycle cost; road traffic safety; vehicle testing
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Special Issue Information

Dear Colleagues,

The ongoing transition towards sustainable transportation has placed electric vehicles (EVs) at the forefront of automotive innovation. Understanding and optimizing the energy consumption and efficiency of these vehicles is crucial for maximizing their range, minimizing operating costs, and reducing their environmental impact. This involves addressing complex challenges related to battery technology, powertrain design, energy management strategies, and real-world driving conditions. The increasing adoption of EVs, driven by environmental concerns and advancements in battery technology, necessitates a comprehensive analysis of their energy performance across diverse operational scenarios. This analysis is essential for developing more efficient vehicles, improving charging infrastructure, and informing policy decisions related to sustainable transportation.

This Special Issue aims to present and disseminate the latest research and developments related to the analysis, modeling, optimization, and real-world assessment of energy consumption and energy efficiency in electric vehicles. It seeks to provide a platform for researchers, engineers, and industry professionals to share their insights and contribute to the advancement of EV technology.

Topics of interest for publication include, but are not limited to, the following:

  • Energy consumption modeling and simulation, including driving cycle analysis, vehicle dynamics, and environmental factors.
  • Real-world energy consumption analysis based on on-road testing and data collection.
  • Impact of driving behavior, traffic conditions, and weather on EV energy consumption.
  • Powertrain efficiency, including electric motor design, power electronics, and transmission systems.
  • Optimization of energy management strategies, including regenerative braking, thermal management, and auxiliary systems.
  • Innovative technologies for improving EV energy efficiency, such as lightweight materials, advanced control algorithms, and novel powertrain architectures.
  • Battery performance and management systems, including battery aging, thermal management, and state-of-charge/state-of-health estimation.
  • Charging infrastructure and its impact on energy efficiency.
  • Impact of smart grid integration and vehicle-to-grid (V2G) technologies on energy consumption.

Dr. Emilia Szumska
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Energies 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 2600 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

  • electric vehicles
  • energy efficiency
  • energy management
  • regenerative braking
  • battery
  • powertrain optimization
  • vehicle-to-grid (V2G)

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Published Papers (5 papers)

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Research

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22 pages, 3019 KB  
Article
Total CO2 Release from Combustion, Electric, and Hybrid Vehicles—A Case Study for Latin America’s Countries
by Robert E. Rockwood, Ana Vassileva Borissova and Klaus Lieutenant
Energies 2025, 18(24), 6623; https://doi.org/10.3390/en18246623 - 18 Dec 2025
Viewed by 174
Abstract
This study investigates the total carbon dioxide (CO2) emissions from various types of passenger vehicles in five Latin American countries: Argentina, Brazil, Ecuador, Mexico, and Paraguay. The aim was to analyze to which degree CO2 output can be reduced in [...] Read more.
This study investigates the total carbon dioxide (CO2) emissions from various types of passenger vehicles in five Latin American countries: Argentina, Brazil, Ecuador, Mexico, and Paraguay. The aim was to analyze to which degree CO2 output can be reduced in Latin America by switching from petrol cars to electric cars. The vehicles analyzed include petrol-driven cars, short-, mid-, and long-range battery electric vehicles, fuel cell electric vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles. The study examines the total CO2 emissions including battery production, vehicle manufacturing, and their operation, considering the energy grid mix of the selected countries for the year 2023. Using experimental data and considering production conditions yields more reliable results than previous studies. The results indicate that battery cars with the shortest cruising range using batteries produced in Europe and/or America generate the lowest levels of CO2 emissions, regardless of the energy mix. However, the emission values vary across different countries. In countries with a predominant share of renewable energy for the electricity generation, such as Paraguay, Brazil, and Ecuador, battery cars are the most effective in reducing overall CO2 emissions. Conversely, in countries like Argentina and Mexico, where renewable energy sources constitute a smaller share of the energy mix, the use of electric vehicles yields only a minor reduction in CO2 output, while emissions of long-range vehicles with batteries produced in Asia even exceed those of internal combustion engine vehicles. Therefore, eco-friendly electricity generation is a prerequisite for eco-friendly use of electric cars and should therefore be the goal of every country. Full article
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48 pages, 3535 KB  
Article
Artificial Intelligence in the Analysis of Energy Consumption of Electric Vehicles
by Boucar Diouf
Energies 2025, 18(23), 6338; https://doi.org/10.3390/en18236338 - 2 Dec 2025
Viewed by 558
Abstract
In the analysis of electric vehicle (EV) energy consumption, three main approaches are commonly used: physics-based models, artificial intelligence (AI) models, and hybrid frameworks that combine both. This combination enables more accurate estimations of EV energy consumption under diverse operating conditions, while also [...] Read more.
In the analysis of electric vehicle (EV) energy consumption, three main approaches are commonly used: physics-based models, artificial intelligence (AI) models, and hybrid frameworks that combine both. This combination enables more accurate estimations of EV energy consumption under diverse operating conditions, while also supporting applications in eco-driving, route planning, and urban energy management. Accurate analysis and prediction of EV energy consumption are critical for vehicle design, route planning, grid integration, and range anxiety. Recent advances in AI, notably machine learning (ML) and deep learning (DL), enable data-driven models that capture complex interactions among driving behavior, vehicle characteristics, road topology, traffic, and environmental conditions. This paper reviews the state of the art and presents a structured methodology for building, validating, and deploying AI models for EV energy consumption and efficiency analysis. Features, model architectures, performance metrics, explainability techniques, and system-level applications are discussed. Full article
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36 pages, 3476 KB  
Article
Is the Grid Ready for the Electric Vehicle Transition?
by Boucar Diouf
Energies 2025, 18(17), 4730; https://doi.org/10.3390/en18174730 - 5 Sep 2025
Viewed by 2710
Abstract
The advancement of electric mobility undoubtedly presents a chance to reduce carbon emissions in road transport and ideally mitigate global warming. The significant and ongoing swift growth in the uptake of electric vehicles (EVs) clearly demonstrates a successful technological advancement; however, it comes [...] Read more.
The advancement of electric mobility undoubtedly presents a chance to reduce carbon emissions in road transport and ideally mitigate global warming. The significant and ongoing swift growth in the uptake of electric vehicles (EVs) clearly demonstrates a successful technological advancement; however, it comes with significant obstacles, particularly regarding the grids’ ability to provide adequate energy and, more importantly, a sufficient installed capacity to manage potential spikes during massive EV charging. Another significant challenge for nations aiming for 100% registrations made of EVs is the S-curve that accompanies their adoption. The S-curve illustrates three primary phases, one of which features a swift increase in the EV fleet, and this phase is likely to surpass grid investments and enhancements in many countries. This manuscript discusses a study on grid preparedness for the EV transition, addressing potential challenges, the benefits of public charging stations, particularly in densely populated regions, and the incorporation of renewable energy. Renewable energy offers the chance to alleviate the pressure on grids, provided that charging behaviors correspond with generation times. There is a need for progress in battery technology to replace classical gas stations with standalone solar or wind powered charging stations. This manuscript showcases this particular scenario in the United States of America (U.S.). Full article
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31 pages, 2741 KB  
Article
Power Flow Simulation and Thermal Performance Analysis of Electric Vehicles Under Standard Driving Cycles
by Jafar Masri, Mohammad Ismail and Abdulrahman Obaid
Energies 2025, 18(14), 3737; https://doi.org/10.3390/en18143737 - 15 Jul 2025
Cited by 1 | Viewed by 2010
Abstract
This paper presents a simulation framework for evaluating power flow, energy efficiency, thermal behavior, and energy consumption in electric vehicles (EVs) under standardized driving conditions. A detailed Simulink model is developed, integrating a lithium-ion battery, inverter, permanent magnet synchronous motor (PMSM), gearbox, and [...] Read more.
This paper presents a simulation framework for evaluating power flow, energy efficiency, thermal behavior, and energy consumption in electric vehicles (EVs) under standardized driving conditions. A detailed Simulink model is developed, integrating a lithium-ion battery, inverter, permanent magnet synchronous motor (PMSM), gearbox, and a field-oriented control strategy with PI-based speed and current regulation. The framework is applied to four standard driving cycles—UDDS, HWFET, WLTP, and NEDC—to assess system performance under varied load conditions. The UDDS cycle imposes the highest thermal loads, with temperature rises of 76.5 °C (motor) and 52.0 °C (inverter). The HWFET cycle yields the highest energy efficiency, with PMSM efficiency reaching 92% and minimal SOC depletion (15%) due to its steady-speed profile. The WLTP cycle shows wide power fluctuations (−30–19.3 kW), and a motor temperature rise of 73.6 °C. The NEDC results indicate a thermal increase of 75.1 °C. Model results show good agreement with published benchmarks, with deviations generally below 5%, validating the framework’s accuracy. These findings underscore the importance of cycle-sensitive analysis in optimizing energy use and thermal management in EV powertrain design. Full article
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Review

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22 pages, 2524 KB  
Review
Regenerative Braking Systems in Electric Vehicles: A Comprehensive Review of Design, Control Strategies, and Efficiency Challenges
by Emilia M. Szumska
Energies 2025, 18(10), 2422; https://doi.org/10.3390/en18102422 - 8 May 2025
Cited by 15 | Viewed by 18686
Abstract
Regenerative braking systems (RBS enhance energy efficiency and range in electric vehicles (EVs) by recovering kinetic energy during braking for storage in batteries or alternative systems. This literature review examines RBS advancements from 2005 to 2024, focusing on system design, control strategies, energy [...] Read more.
Regenerative braking systems (RBS enhance energy efficiency and range in electric vehicles (EVs) by recovering kinetic energy during braking for storage in batteries or alternative systems. This literature review examines RBS advancements from 2005 to 2024, focusing on system design, control strategies, energy storage technologies, and the impact of external and kinematic factors on recovery efficiency. Based on a systematic analysis of 89 peer-reviewed articles from Scopus, it highlights a shift from basic PID controllers to advanced predictive algorithms like Model Predictive Control (MPC) and machine learning approaches. Technologies such as brake-by-wire and in-wheel motors improve safety and stability, with the latter excelling in all-wheel-drive setups over single-axle configurations. Hybrid Energy Storage Systems (HESS), combining batteries with supercapacitors or kinetic accumulators, address power peak demands, though cost and complexity limit scalability. Challenges include high computational requirements, component reliability in harsh conditions, and lack of standardized testing. Research gaps involve long-term degradation, autonomous vehicle integration, and driver behavior effects. Future work should explore cost-effective HESS, robust predictive controls for autonomous EVs, and standardized frameworks to enhance RBS performance and support sustainable transportation. Full article
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