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Hybrid Power for Mobile Systems
Published in Yatish T. Shah, Hybrid Power, 2021
The literature also considers power split for the analysis of the through-the-road (TTR) architecture, a subcategory of parallel architecture. The split-parallel architecture for TTR and its control challenges are detailed in the work by Zulkifli et al. [54]. Miller [55] employed power split architecture as it provides better liberty of power control. He also showed that electronic continuous variable transmission (e-CVT) was more efficient than mechanical continuous variable transmission (CVT). Cheng and Dong [56] simulated a model of the power split PHEV powertrain and a TTR hybrid electric powertrain and their prototypes were investigated based on various parameters. A quasi-static model was used to investigate and evaluate vehicle performance, fuel economy, emissions, and supervisory control of the passenger car. A low-frequency vehicle powertrain dynamics model was used to evaluate the vehicle dynamics, acceleration, and braking performance of a racecar. Several other aspects of patterns of power flow are reviewed in detail by Singh et al. [6].
Introduction
Published in Georg Rill, Abel Arrieta Castro, Road Vehicle Dynamics, 2020
Georg Rill, Abel Arrieta Castro
Vehicle dynamics are a part of engineering primarily based on classical mechanics but may also involve control theory, physics, electrical engineering, chemistry, communications, psychology, etc. Here, the focus is laid on ground vehicles supported by wheels and tires. Vehicle dynamics encompass the interaction of the following: DriverVehicleLoadEnvironment
On the benefit of smart tyre technology on vehicle state estimation
Published in Vehicle System Dynamics, 2022
Victor Mazzilli, Davide Ivone, Stefano De Pinto, Leonardo Pascali, Michele Contrino, Giulio Tarquinio, Patrick Gruber, Aldo Sorniotti
From a vehicle dynamics perspective, tyres are in the most privileged position as they are the only component that is in contact with the road surface. Sensing systems directly located in the tyre are a promising technology to obtain useful information for vehicle dynamics control and/or state estimation. Accordingly, the CyberTM Tyre project of Pirelli Tyre S.p.A. is developing an innovative tyre sensing system that is able to: (i) measure the relevant variables through a tri-axial accelerometer embedded in the inner liner of the tyre carcass; (ii) condition the collected signals during the tyre rolling motion; and (iii) transmit them to a receiver located on the vehicle. The outputs of the specific smart tyre system are: (a) the vertical and longitudinal tyre forces, detected once per wheel rotation, which represent the smart tyre outputs used in this study; (b) a flag variable that provides indication of incipient hydroplaning, see [25]; and (c) indication of the installed tyre model, i.e. the so-called tyre ID function, which allows automated re-tuning of the tyre parameters included in the vehicle state estimators and controllers when the tyres are replaced with a different model. The algorithms for the generation of the variables in (a)–(c), developed through indoor calibration tests in controlled environment, are beyond the scope of this paper, and are described in [26].
A data-driven framework for forecasting transient vehicle thermal performances
Published in Numerical Heat Transfer, Part B: Fundamentals, 2023
Chuanning Zhao, Changsu Kim, Yoonjin Won
The knowledge to transient vehicle dynamics is essential for optimizing vehicle design [1,2] and enhancing driving stability [3]. Vehicle dynamics refer to the responsive motions and behaviors of its components, such as engine, transmission, brakes, steering, and tire, while operating. The tire, being one of the primary components that directly interacts with the road, and its dynamics are key components in affecting the overall vehicle dynamics. Tire dynamics, such as tire deformation, contacting forces, and tire spatial-temporal temperature distribution, are influenced by various operating conditions including road [4,5], weather [6], and vehicle loads and speeds [7,8]. Most importantly, tire produces and is strongly affected by heat generations through tire-road friction at tire surface and rolling resistance via cyclic deformation of a whole tire. As a result, varying heat transfer flows at different tire radial positions contribute to the variation in tire spatial temperature distribution. Previous studies recognize the non-linear dependency of tire rubber mechanical characteristics on tire temperatures [9–11]. Due to this temperature dependency of tire mechanical characteristics, in return, the intensity of tire-road friction also varies with different tire temperature levels [12,13]. To analyze the coupled heat transport problem in tire, we need to understand the relations between the heat generations and transfer through ambient air convection, exhausted gas convection, tire tread radiation and convection, tread-road conduction, inner liner and rim conduction, and tire cyclic rolling deformation heat generation and friction work heat generation [14–16]. Typically, radiation heat transfer from the tire tread is neglected due to its magnitude being around ten times smaller compared to convective heat transfer.
Smart structures with embedded flexible sensors fabricated by fused deposition modeling-based multimaterial 3D printing
Published in International Journal of Smart and Nano Materials, 2022
Huilin Ren, Xiaodan Yang, Zhenhu Wang, Xuguang Xu, Rong Wang, Qi Ge, Yi Xiong
Tire-road contacts are the only interface between vehicles and roads and thus significantly influence vehicle dynamics. Sensing these tire-road interactions can provide valuable information for the development of autonomous vehicles [39]. However, standard tires are still passive vehicle components that cannot perceive their states, e.g. the vertical load. In the second design case, we demonstrate the use of the proposed design and fabrication workflow for developing a smart tire with both load-bearing and sensing functions.