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Editorial

Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact

Department of Industrial Engineering, University of Naples Federico II, 80131 Naples, Italy
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Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(4), 2034; https://doi.org/10.3390/app12042034
Submission received: 7 February 2022 / Accepted: 11 February 2022 / Published: 16 February 2022
Recent trends in vehicle engineering prove the great effort that scientists and industries have made in seeking solutions to enhance both the performance and the safety of vehicular systems. Physical models concerning vehicle–ground interaction, control strategies for the vehicle and its subsystems, and new technologies are developing all over the world for this purpose. The published Special Issue contributed to the study of modern vehicle dynamics, attracting recent experimental and in-simulation advances that are the basis for the current technological growth and for future mobility. Such areas involve research, studies, and projects coming from both vehicle dynamics and contact mechanics, with the perspective to embrace activities aiming to enhance vehicle performance in terms of handling, comfort, and adherence and to examine safety optimization also in the emerging contexts of smart, connected, and autonomous driving.
The accepted scientific contributions covered topics concerning new results and studies in the following areas related to the interaction of vehicle dynamics and the ground:
  • Physical models concerning tire–road and vehicle–ground interaction: In particular, [1] refers to new developments in airless (or non-pneumatic) tires, representing a significant perspective in the future evolution of such components. Regarding tires, [2] proposes strategies to optimize tread wear and minimize the dispersion of rubber particles, properly acting on wheel and suspension setup. Moreover, [3,4] focus on materials characterization and local contact phenomena, analyzing, respectively, innovative polynomial formulations for the reproduction of viscoelastic compounds’ behaviors and the adhesive effects of dimpled textures in contact with flat surfaces. Finally, [5] proposes artificial neural networks to identify the parameters of Pacejka’s Magic Formula tire models, widely adopted in the context of automotive simulations;
  • Experimental activities aimed at the investigation and the comprehension of interaction phenomena: Among the published papers, some developed an approach based on the macroscale effects, analyzing the whole vehicle data as proposed in [6], mainly centered on ride analysis on wavy profiles; In ref. [7], accounting for suspension sensitivity to road roughness, longitudinal speed, and vehicle segment; and in [8], switching to the effects on the directional capabilities. Some other authors worked on the microscale, accounting for indentation, friction, and contact mechanics at the ground, as investigated in [9], relating to gravel surfaces and noise, and in [4], focusing also on aspects related to adhesive local contact phenomena;
  • Control strategies focused on vehicle performance enhancement, in terms of handling/grip, comfort, and safety: In ref. [10], a safety control strategy is proposed, acting on the steering system and differential, useful for performing emergency maneuvers for obstacle avoidance; In ref. [11], a central predictive control system is proposed, acting on a non-linear, model-based predictive algorithm; and in [12], the onboard implementation of friction estimation, in autonomous driving and vehicle following applications, is illustrated. The authors of one of the submitted papers also focused on traffic contexts, in particular reporting a case study involving Duisburg Ring environment [13];
  • Innovative technologies to improve the safety and performance of the vehicle and its subsystems, such as adopting active/semiactive suspension in in-wheel architectures, enhancing the roadholding [14] and stability-oriented steering systems in articulated vehicle applications [15];
  • Identification of vehicle and tire/wheel model parameters and state with innovative methodologies and algorithms, based on machine learning techniques, as described in [5];
  • Implementation of real-time software, logics, and models in onboard architectures [13] with a main target involving applications oriented towards autonomous driving and connected mobility scenarios;
  • Studies and analyses oriented toward the correlation among the factors affecting vehicle consumptions, such as in powertrain architectures in electric mobility described in [16], or performance and stability, with the target to propose strategies for the minimization of undesired phenomena, as proposed by the authors of the article [2], who focused on tire tread wear;
  • Application use cases in scenarios not only concerning car and conventional four-wheeled vehicles or common asphalt roads. The published papers represent advances in vehicle dynamics also involving off-road vehicles, as analyzed in [9], heavy articulated vehicles [15], or motorcycles, for which [17] proposed a study on their stability, developing an innovative approach based on the so-called screw axis instead of the usual phase plane.

Author Contributions

Conceptualization, F.F.; writing—original draft preparation, F.F.; writing—review and editing, A.S. and A.G.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Genovese, A.; Garofano, D.; Sakhnevych, A.; Timpone, F.; Farroni, F. Static and Dynamic Analysis of Non-Pneumatic Tires Based on Experimental and Numerical Methods. Appl. Sci. 2021, 11, 11232. [Google Scholar] [CrossRef]
  2. Papaioannou, G.; Jerrelind, J.; Drugge, L. Multi-Objective Optimisation of Tyre and Suspension Parameters during Cornering for Different Road Roughness Profiles. Appl. Sci. 2021, 11, 5934. [Google Scholar] [CrossRef]
  3. Tassara, M.; Grigoriadis, K.; Mavros, G. Empirical Models for the Viscoelastic Complex Modulus with an Application to Rubber Friction. Appl. Sci. 2021, 11, 4831. [Google Scholar] [CrossRef]
  4. Papangelo, A. On the Effect of a Rate-Dependent Work of Adhesion in the Detachment of a Dimpled Surface. Appl. Sci. 2021, 11, 3107. [Google Scholar] [CrossRef]
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  6. Wedig, W. Speed Oscillations of a Vehicle Rolling on a Wavy Road. Appl. Sci. 2021, 11, 10431. [Google Scholar] [CrossRef]
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  9. Žuraulis, V.; Sivilevičius, H.; Šabanovič, E.; Ivanov, V.; Skrickij, V. Variability of Gravel Pavement Roughness: An Analysis of the Impact on Vehicle Dynamic Response and Driving Comfort. Appl. Sci. 2021, 11, 7582. [Google Scholar] [CrossRef]
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MDPI and ACS Style

Farroni, F.; Genovese, A.; Sakhnevych, A. Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact. Appl. Sci. 2022, 12, 2034. https://doi.org/10.3390/app12042034

AMA Style

Farroni F, Genovese A, Sakhnevych A. Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact. Applied Sciences. 2022; 12(4):2034. https://doi.org/10.3390/app12042034

Chicago/Turabian Style

Farroni, Flavio, Andrea Genovese, and Aleksandr Sakhnevych. 2022. "Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact" Applied Sciences 12, no. 4: 2034. https://doi.org/10.3390/app12042034

APA Style

Farroni, F., Genovese, A., & Sakhnevych, A. (2022). Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact. Applied Sciences, 12(4), 2034. https://doi.org/10.3390/app12042034

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