Vehicle Operations

This review article examines the deterministic control model and centralized control model, the types of EV models, and their tabular comparison. Additionally, expressing the communication standards to deal with compatibility challenges in charging stations, the effects of EV integration with the power grid, and various methods such as smart charging, dumb charging, and flexible charging are the main goals of this review article.

The article delves into the evolution of battery chemistries, energy densities, and thermal management systems, which collectively impact battery life and overall vehicle longevity. Additionally, insights into battery recycling and second-life applications are discussed as essential strategies to mitigate environmental impacts and enhance the sustainability of EV operations.

This paper presents a novel Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) infrastructure designed to optimize energy flow between electric vehicles and the electrical grid. The system is equipped with a bidirectional converter and a three-phase inverter/rectifier, minimizing the number of switches to reduce weight and size. A model predictive control (MPC) scheme is introduced to regulate the converter's operation and maintain grid stability, while also functioning as an active power filter when idle. Simulation results using MATLAB/Simulink demonstrate the system's efficiency, verifying its ability to manage energy transfer and mitigate harmonic distortion effectively.

In this study, the basic structure of the pure electric command vehicle is studied, the main components of the command vehicle power system, namely the selection of the drive motor and the power battery, are analyzed, and the main parameters of the drive motor and the power battery are designed and calculated. The calculation results show that the power and transmission system developed in this paper meets the design requirements, and the design scheme is feasible and reasonable.

This article explores battery health monitoring in electric vehicles (EVs) using machine learning to address challenges in battery durability and enable new business models. It introduces a virtual battery prototype that applies supervised learning methods, such as Random Forest and Deep Neural Network regression, to estimate real-time energy slack and monitor battery health. The study also presents a carbon balance optimization application, aiming to minimize carbon emissions and charging costs for EV fleets through grid optimization. The model enables continuous battery health monitoring, opening opportunities for innovative commercial use cases for EV users, fleet managers, and grid operators.

The scope of this study is to demonstrate that on-board electric powertrains with torsional dynamics of the half-shafts have the potential for effective compensation, thanks to the road profile preview. This paper presents a proof-of-concept nonlinear model predictive controller (NMPC) with road preview, which is assessed with a validated simulation model of an all-wheel drive electric vehicle. Three powertrain layouts are considered, with four in-wheel, four on-board, and two on-board electric machines. The control function is evaluated along multiple manoeuvres, through comfort-related key performance indicators (KPIs) that, for the four on-board layout along a road step test at 40 km/h, highlight >80% improvements. Finally, the real-time implementability of the algorithms is demonstrated, and preliminary experiments are conducted on an electric quadricycle prototype, with more than halved oscillations of the relevant variables.

The aim of the present work is to establish which are the main driveline components affecting the filtering behavior of the transmission and how their parameters can be tuned in order to improve the vehicle ability to respond to driver’s different demands without negative impact on his comfort. A complete nonlinear coupled torsional and longitudinal vehicle dynamic model is proposed to this end. The model is validated both in time and frequency domain and allows linearization of its nonlinear components.