Feature Review Papers on Trends and Challenges in Automotive Engineering

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 10739

Special Issue Editors

DIMEG, Università della Calabria, 87036 Rende, Italy
Interests: gearing and transmissions; vehicle dynamics; numerical modelling of composite material for NVH simulations; kinematic synthesis and analysis of planar mechanisms
Special Issues, Collections and Topics in MDPI journals
Department of Industrial Engineering, University of Naples Federico II, Via Claudio, 21-80125 Naples, Italy
Interests: dynamics and the control of mechanical systems; engineering; material science
Special Issues, Collections and Topics in MDPI journals
LMSD Research Group, Department of Mechanical Engineering, KU Leuven, Celestijnenlaan 300, 3001 Leuven, Belgium
Interests: mechanical engineering; multibody simulation; structural dynamics; model reduction; state-estimation
Department of Mechanical, Energy and Management, University of Calabria, 87036 Rende, Italy
Interests: mixed and virtual prototyping; model-based engineering; control engineering and mechatronics

Special Issue Information

Dear Colleagues,

A key innovation driver for the automotive industry is the need to satisfy customer demand for vehicles with improved performance, while at the same time meeting constraints and requirements set by regulatory bodies that are aimed at achieving green and safe mobility integrated into smart environments (smart roads, smart cities, etc.).

The goal of this Special Issue is to explore current trends in automotive engineering and the related scientific and technological challenges and solutions. By collecting feature reviews by leading scientists and industrial experts, this Special Issue will provide the interested audience with a comprehensive view on the maturity level of the state-of-the-art methods and technologies that will pave the way for the next-generation of road vehicles.

Prof. Dr. Domenico Mundo
Dr. Francesco Timpone
Dr. Frank Naets
Dr. Francesco Cosco
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Machines is an international peer-reviewed open access monthly 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

  • VR and driving simulators
  • AI and Machine Learning in the vehicle development cycle
  • connected and autonomous vehicles in smart environments
  • advanced materials and manufacturing
  • hybridization and electrification
  • active and passive safety systems

Published Papers (3 papers)

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Research

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17 pages, 2409 KiB  
Article
Indirect Estimation of Tire Pressure on Several Road Pavements via Interacting Multiple Model Approach
by Renato Brancati and Francesco Tufano
Machines 2022, 10(12), 1221; https://doi.org/10.3390/machines10121221 - 15 Dec 2022
Cited by 3 | Viewed by 1460
Abstract
Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, [...] Read more.
Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, due to technical and economic reasons. Cost-effective solutions with real-time estimation of tire pressure are generally less accurate and reliable than direct ones. Dynamical estimators based on a suspension model need road surface topology information to compute disturbances on the suspension system as an input, which is typically unknown. This paper proposes an innovative approach to estimate tire pressure indirectly, without actual road surface roughness information. A vertical suspension dynamic model is used to build several unscented Kalman filters, parametrised around different road surface topologies. These estimators are combined following the Interacting Multiple Model approach, which gives an acceptable estimation of tire stiffness through a weighted average obtained from a probabilistic model. A known linear static relationship between the tire stiffness and inflation pressure is utilized to indirectly estimate the tire inflation pressure. A Monte Carlo analysis has been performed on a wide range of driving scenarios and vehicle manoeuvres. The results of the estimation have been compared to those of a single unscented Kalman filter, in order to validate the effectiveness of the proposed solution and to highlight the improved performances in monitoring tire pressure. Full article
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19 pages, 5700 KiB  
Article
Hydrogen-Fuel Cell Hybrid Powertrain: Conceptual Layouts and Current Applications
by Petronilla Fragiacomo, Matteo Genovese, Francesco Piraino, Orlando Corigliano and Giuseppe De Lorenzo
Machines 2022, 10(12), 1121; https://doi.org/10.3390/machines10121121 - 26 Nov 2022
Cited by 10 | Viewed by 5076
Abstract
Transportation is one of the largest sources of CO2 emissions, accounting for more than 20% of worldwide emissions. However, it is one of the areas where decarbonization presents the greatest hurdles, owing to its capillarity and the benefits that are associated with [...] Read more.
Transportation is one of the largest sources of CO2 emissions, accounting for more than 20% of worldwide emissions. However, it is one of the areas where decarbonization presents the greatest hurdles, owing to its capillarity and the benefits that are associated with the use of fossil fuels in terms of energy density, storage, and transportation. In order to accomplish comprehensive decarbonization in the transport sector, it will be required to encourage a genuine transition to low-carbon fuels and the widespread deployment of the necessary infrastructures to allow for a large-scale innovation. Renewable hydrogen shows potential for sustainable transportation applications, whether in fuel cell electric vehicles (FCEVs), such as automobiles, trucks, and trains, or as a raw material for ship and airplane synthetic fuels. The present paper aims to present how hydrogen-fuel cell hybrid powertrains for road vehicles work in terms of conceptual layouts and operating strategies. A comprehensive overview of real and current applications is presented, concerning existing prototypes and commercially available vehicles, with a focus on the main key performance indicators, such as efficiency, mileage, and energy consumption. Full article
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Review

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25 pages, 3606 KiB  
Review
Review on Torque Distribution Scheme of Four-Wheel In-Wheel Motor Electric Vehicle
by Shuwen He, Xiaobin Fan, Quanwei Wang, Xinbo Chen and Shuaiwei Zhu
Machines 2022, 10(8), 619; https://doi.org/10.3390/machines10080619 - 28 Jul 2022
Cited by 12 | Viewed by 3388
Abstract
In-wheel motor electric vehicles have the advantages of independently controllable four-wheel torque, high energy utilization rate, and fast motor response speed, which greatly reduces the curb weight of the vehicle and simplifies the structure of the vehicle, making it an expert at home [...] Read more.
In-wheel motor electric vehicles have the advantages of independently controllable four-wheel torque, high energy utilization rate, and fast motor response speed, which greatly reduces the curb weight of the vehicle and simplifies the structure of the vehicle, making it an expert at home and abroad research hotspots. However, the in-wheel motor independently drives the electric vehicle. The in-wheel motor directly drives the vehicle, and the motion states of each wheel are independent of each other; that is, each wheel can be independently driven by wire control, which puts forward higher requirements for the torque distribution control of the entire vehicle. Starting from the driving form of the car, this paper focuses on the design of the torque distribution scheme of the in-wheel motor by experts and scholars in the past, such as the use of genetic algorithm, BP neural network, particle swarm algorithm, and fuzzy control algorithm to distribute the torque of the in-wheel motor, and the research on vehicle economy and stability under torque distribution optimization is reviewed. The future development direction of in-wheel motor torque distribution is prospected. Full article
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