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Advancements and Future Trends in Vehicle Electrification and Intelligent Control...
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Advancements and Future Trends in Vehicle Electrification and Intelligent Control Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2741

Special Issue Editors

Dr. Luis M. Castellanos Molina

E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: control techniques for automotive suspension systems; model-predictive control; rapid control prototyping; system identification
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nicola Amati

E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: applied mechanics; automotive applications; electromagnetic
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of vehicle electrification and intelligent control systems is reshaping the future of transportation. This Special Issue aims to present cutting-edge research and emerging trends in electric powertrains, energy management strategies, and AI-driven control mechanisms that enhance vehicle performance, efficiency, and safety. Topics of interest include, but are not limited to, battery technologies, charging infrastructure, hybrid energy systems, autonomous vehicle control, advanced driver assistance systems, and the integration of artificial intelligence in vehicular decision-making processes.

We invite researchers, industry professionals, and practitioners to contribute their latest findings and insights to this Special Issue. By fostering interdisciplinary collaboration, we seek to address challenges and opportunities in the transition toward smarter, more sustainable, and highly automated transportation systems.

We are delighted to invite you to contribute to our Special Issue, Advancements and Future Trends in Vehicle Electrification and Intelligent Control Systems. As the automotive industry continues to embrace electrification and intelligent control, this Special Issue will serve as a platform to showcase pioneering research and technological breakthroughs. Your contributions—whether theoretical advancements, experimental studies, or real-world applications—will help shape the future of mobility.

We look forward to receiving your valuable submissions and sharing innovative ideas with the global research community.

Dr. Luis M. Castellanos Molina
Prof. Dr. Nicola Amati
Guest Editors

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. Applied Sciences 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 2400 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

  • vehicle electrification
  • electric powertrains
  • battery technologies
  • energy management systems
  • charging infrastructure
  • hybrid and electric vehicles (HEVs/EVs)
  • autonomous vehicles
  • virtual sensing
  • advanced driver assistance systems (ADASs)
  • intelligent control systems
  • artificial intelligence in transportation
  • machine learning for vehicle control
  • vehicle-to-everything (V2X) communication
  • cybersecurity in smart vehicles
  • smart grid integration
  • sustainable transportation

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Published Papers (2 papers)

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Research

16 pages, 6233 KB  
Article
A Tire Temperature Adaptive Extended Kalman Filter for Sideslip Angle Estimation: Experimental Validation on a Race Track
by Andrea Masoero, Raffaele Manca, Luis M. Castellanos Molina and Andrea Tonoli
Appl. Sci. 2026, 16(1), 310; https://doi.org/10.3390/app16010310 - 28 Dec 2025
Viewed by 1022
Abstract
Real-time estimation of vehicle sideslip angle is essential for both safety and performance applications. This study presents a temperature-adaptive Extended Kalman Filter (EKF) that estimates the sideslip angle of a racing vehicle by integrating dynamic and kinematic information. A temperature-dependent Pacejka tire model, [...] Read more.
Real-time estimation of vehicle sideslip angle is essential for both safety and performance applications. This study presents a temperature-adaptive Extended Kalman Filter (EKF) that estimates the sideslip angle of a racing vehicle by integrating dynamic and kinematic information. A temperature-dependent Pacejka tire model, derived directly from track tests, is embedded in a 3-degree-of-freedom dual-track vehicle model and used within the EKF to compensate for temperature-induced variations in tire behavior. The adaptive model parameters are identified from standard on-track maneuvers conducted at different tire temperatures, without the need for additional indoor rig testing. Experimental validation on a race track demonstrates that incorporating tire temperature adaptation and combining dynamic and kinematic estimation significantly enhance estimation accuracy, particularly underow-grip and high-performance driving conditions attested by a reduction of 40–50% in RMS error and a further reduction in maximum absolute error. Full article
(This article belongs to the Special Issue Advancements and Future Trends in Vehicle Electrification and Intelligent Control Systems)
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29 pages, 5722 KB  
Article
Robust Path-Tracking Control for Autonomous Vehicles: A Model-Reference-Adaptive-Control-Based Integrated Chassis Control Strategy
by Siyeong Park, Taeyoung Oh, Jeesu Kim and Jinwoo Yoo
Appl. Sci. 2025, 15(23), 12387; https://doi.org/10.3390/app152312387 - 21 Nov 2025
Viewed by 1249
Abstract
Autonomous vehicles are often subjected to disturbances that compromise path-tracking accuracy and stability. Traditional chassis controllers that rely on fixed vehicle models exhibit performance limitations under such uncertainties. To address this challenge, we propose an adaptive integrated chassis control strategy that combines a [...] Read more.
Autonomous vehicles are often subjected to disturbances that compromise path-tracking accuracy and stability. Traditional chassis controllers that rely on fixed vehicle models exhibit performance limitations under such uncertainties. To address this challenge, we propose an adaptive integrated chassis control strategy that combines a linear quadratic regulator (LQR) and a model reference adaptive control (MRAC) framework. The LQR component generates nominal control commands, while the MRAC framework compensates in real time for model uncertainties and external disturbances. Simulation studies conducted in CarMaker and MATLAB/Simulink indicate that the proposed controller substantially improves path-tracking performance. Compared with conventional methods, the proposed controller reduces the root mean square error, peak error, and integral of the absolute error by up to 25.2%, 33.5%, and 34.6%, respectively. Overall, the proposed adaptive chassis controller shows enhanced vehicle robustness and stability in simulation under challenging driving conditions. Full article
(This article belongs to the Special Issue Advancements and Future Trends in Vehicle Electrification and Intelligent Control Systems)
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