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Recent Developments in Electric Vehicles, Second Edition
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Recent Developments in Electric Vehicles, Second Edition

A Special Issue of Applied Sciences (ISSN 2076-3417) belonging to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 August 2026) | Viewed by 1978

Editor

Prof. Dr. Jingyang Fang

E-Mail Website
Guest Editor
School of Control Science and Engineering, Shandong University, Jinan 250061, China
Interests: power electronics; power systems; digital control; energy storage; renewable energies; stability and power quality of grid-tied power converters
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electric and plug-in hybrid electric vehicles produce significantly lower noises and less greenhouse gas emissions than conventional fossil fuel-powered vehicles. Additionally, vehicles powered through electricity demonstrate improved performance and efficiency. Because of this, there is an ongoing trend of electric propulsion replacing engine propulsion. However, the high-efficiency charging and management of battery storage challenge global engineers and experts. In parallel, the smart control of charging and/or discharging will greatly aid grid operators and thus enable the coordination of large numbers of electric vehicles. This Special Issue focuses on the recent developments being made in electric vehicles, particularly those related to power and energy. It aims to lay a foundation for the further development of electric and hybrid electric vehicles in future renewable-dominated power systems.

Prof. Dr. Jingyang Fang
Guest Editor

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Keywords

  • power architectures of electric drivetrains
  • multilevel converters in electric vehicles
  • battery state-of-charge (SOC)/health (SOH) estimation
  • battery management systems
  • wireless power chargers
  • vehicle-to-grid (V2G) services
  • optimization and coordination of charging for multiple vehicles
  • autonomous driving systems and enabling components

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Published Papers (3 papers)

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Research

33 pages, 6023 KB  
Article
Observability-Aware Estimation of Tradeable Vehicle-to-Grid Capacity from Heterogeneous Charger Telemetry
by Róbert Štefko, Vladimír Szomosi, Marek Bobček, Jozef Király, Zsolt Čonka and Erik Chabreček
Appl. Sci. 2026, 16(19), 9410; https://doi.org/10.3390/app16199410 - 22 Sep 2026
Viewed by 205
Abstract
Vehicle-to-grid (V2G) aggregators must commit energy and power that connected vehicles can actually deliver, yet they often observe only charger-side telemetry, and vehicle-reported state of charge (SOC) is optional or non-authoritative. This paper proposes an observability-aware framework for estimating tradeable V2G capacity: each [...] Read more.
Vehicle-to-grid (V2G) aggregators must commit energy and power that connected vehicles can actually deliver, yet they often observe only charger-side telemetry, and vehicle-reported state of charge (SOC) is optional or non-authoritative. This paper proposes an observability-aware framework for estimating tradeable V2G capacity: each session is classified by its measurement boundary, channels, sampling, latency, and setpoint control, then mapped to the battery through uncertain conversion paths. The estimator outputs conservative safe energy and safe power rather than absolute SOC, treats vehicle-reported values as noisy hints, and abstains when observability is insufficient. A reproducible synthetic study shows that regularization and a split-conformal margin bring the bound to the 95% target with a finite-sample guarantee under within-regime exchangeability, and that the required capacity haircut grows from about 2.6 through 4.3 to 6.5 SOC points as observability degrades. Coverage alone does not distinguish the method, since any conformalized predictor reaches the target; the observability-aware bound adds tradeable capacity at that coverage, and its advantage grows as telemetry degrades. End-to-end market deliverability is established only in synthesis: a laboratory proof of concept on one bidirectional charger with four production vehicles demonstrates AC-boundary telemetry ingestion and capability assignment, but measures realized throughput after the fact rather than a bound committed before dispatch. Full article
(This article belongs to the Special Issue Recent Developments in Electric Vehicles, Second Edition)
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33 pages, 4725 KB  
Article
Performance Comparison of Event-Triggered RLS-EKF, EKF, CKF and SR-CKF for EV Battery SOC Estimation During Interference Bursts: A Simulation-Based Study
by Miin-Jong Hao and Yu-Shuo Yang
Appl. Sci. 2026, 16(14), 7095; https://doi.org/10.3390/app16147095 - 15 Jul 2026
Viewed by 417
Abstract
Accurate state-of-charge (SOC) estimation is essential for preventing battery degradation, improving energy management, and providing reliable driving-range predictions in electric vehicles (EVs). The extended Kalman filter (EKF) is a widely adopted model-based estimation technique and remains an industry-standard approach in EV battery management [...] Read more.
Accurate state-of-charge (SOC) estimation is essential for preventing battery degradation, improving energy management, and providing reliable driving-range predictions in electric vehicles (EVs). The extended Kalman filter (EKF) is a widely adopted model-based estimation technique and remains an industry-standard approach in EV battery management systems (BMS). However, its performance can be degraded by model nonlinearities, parameter uncertainties, measurement noise, and interference bursts commonly encountered in real-world operating environments. To overcome these limitations, this paper proposes an event-triggered adaptive SOC estimation framework that integrates a recursive least squares (RLS) filter with the EKF. In the proposed approach, the RLS filter recursively updates its weighting coefficients in real time to compensate for model uncertainties and measurement disturbances, thereby generating an alternative residual signal for SOC estimation. An event-triggered mechanism dynamically selects the most reliable innovation sequence for updating the EKF state estimate, enhancing estimation robustness under adverse operating conditions. A second-order RC equivalent circuit model (ECM) is employed as the nominal battery model, and a Hybrid Pulse Power Characterization (HPPC)-based current profile is used to evaluate performance over the entire SOC operating range. Extensive simulations are conducted to assess the effectiveness of the proposed event-triggered RLS-EKF algorithm under various noise levels and interference-burst scenarios. The estimation accuracy is compared with that of the conventional EKF, cubature Kalman filter (CKF), and square root cubature Kalman filter (SR-CKF) using root mean square error (RMSE) and mean absolute error (MAE) as performance metrics. Simulation results demonstrate that, under regular noise conditions and short-term interference bursts, the proposed event-triggered RLS-EKF achieves estimation performance comparable to that of the SR-CKF while consistently outperforming the EKF and CKF in both RMSE and MAE. Under long-term interference-burst conditions, the proposed method further surpasses the SR-CKF, achieving approximately 10% improvement in overall estimation accuracy as measured by RMSE and MAE. These results confirm the effectiveness and robustness of the proposed framework, highlighting its potential for practical implementation in advanced EV battery management systems. Full article
(This article belongs to the Special Issue Recent Developments in Electric Vehicles, Second Edition)
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18 pages, 3330 KB  
Article
A Seven-Level Single-DC-Source Inverter with Triple Voltage Gain and Reduced Component Count
by Ziyang Wang, Decun Niu, Jingyang Fang, Minghao Chen, Lei Zhang, Wei Zhang, Dong Wang and Qianli Ma
Appl. Sci. 2026, 16(1), 215; https://doi.org/10.3390/app16010215 - 24 Dec 2025
Cited by 2 | Viewed by 815
Abstract
This paper proposes a novel seven-level switched-capacitor multilevel inverter featuring a shared front-end DC-link structure that achieves triple voltage gain with reduced component count. A distinctive feature of this design is its inherent capacitor voltage self-balancing capability, thereby eliminating the need for complex [...] Read more.
This paper proposes a novel seven-level switched-capacitor multilevel inverter featuring a shared front-end DC-link structure that achieves triple voltage gain with reduced component count. A distinctive feature of this design is its inherent capacitor voltage self-balancing capability, thereby eliminating the need for complex control algorithms typically associated with multilevel converters. Moreover, the topology demonstrates particularly significant advantages in three-phase implementations, where a single DC source, front-end switching devices, and capacitors can be shared across all phases—thus substantially reducing component count and system complexity compared to conventional designs. Additionally, this paper proposes an improved carrier-based modulation strategy for this topology requiring only a single triangular carrier, along with a systematic method for determining optimal capacitance values. Through detailed comparative assessment against state-of-the-art switched-capacitor seven-level inverters, the superior performance characteristics of the proposed topology are clearly demonstrated. Finally, simulation results under various operating conditions are presented and subsequently validated through experimental testing on a laboratory prototype, confirming the practical viability of the proposed solution. Full article
(This article belongs to the Special Issue Recent Developments in Electric Vehicles, Second Edition)
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