energies-logo

Journal Browser

Journal Browser

Advanced Technologies in Electrified Vehicles

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 4392

Special Issue Editors


E-Mail Website
Guest Editor
Beijing Collaborative and Innovative Center for Electric Vehicle, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: hybrid/electric drive integration and energy management; intelligent vehicle design and control

E-Mail Website1 Website2
Guest Editor
School of Electrical Engineering, Anhui Polytechnic University, Wuhu, China
Interests: vehicle environmental perception; vehicle path planning; vehicle tracking control

E-Mail Website
Guest Editor
School of Mechanical Engineering, Beijing Institute of Technology, Haidian District, Beijing 100081, China
Interests: vehicle dynamics control; electric vehicles; energy management; optimal control; automated driving
Chassis Components Technical, China North Vehicle Research Institute, Beijing 100072, China
Interests: advanced driver assistance systems; hybrid electric vehicle control; vehicle system and control

Special Issue Information

Dear Colleagues,

Future vehicles are expected to be electrified. High levels of vehicle electrification is deemed promising for addressing the issues in resource scarcity and pollutant discharge. The characteristic of electric drive configuration also brings the advantages of high dynamic response, expected maneuverability, and improved safety. Recently, the booming advancements in V2X techniques enable more information past and present in electrified vehicles’ application, providing more improved rooms of state estimation, control, and fault diagnosis to further improve operation effects. For example, benefiting from the information of future surrounding vehicles, vehicle motions can be planned beforehand in a safety- and efficiency-oriented manner.

Nevertheless, to make the above happen, several challenges still need to be addressed by research communities. As a multi-component coupling device, highly nonlinear vehicle system dynamics also lead to huge difficulties in state estimation and system control, which limits performance improvements. With the increasing utilization rate in vehicle electrification, the vehicle’s reliability demands are also raised, resulting in the requirements of timely fault diagnosis and effective scheme of fault tolerance. Additionally, under the V2X scenarios, the implementations of expected effects highly rely on the utilization ratio of reliable information, framework applicability of strategies, and so forth.

This Special Issue aims to present and disseminate the latest technologies for design, modelling, estimation, control, and application for all kinds of electrified vehicles.

The topics of interest include but are not confined to:

  • Novel propulsion architectures for electrified vehicles to enhance the effects of energy efficiency and maneuverability.
  • Advanced estimation of vehicular sub-systems’ dynamics (e.g., battery, motors, fuel cells) and short-term/long-term driving conditions, road conditions, motion states, to improve the operation effects.
  • Control strategies, including powertrain power flows optimization, vehicle dynamics control, ecological adaptive cruise control, motion planning, fleet management, and more.
  • Diagnosis and fault-tolerance scheme of energy sources, sensors, and actuators to conduct drive safety, energy economy, lifetime extension, and so on.
  • Exploitation of V2X techniques in parameters sizing, state estimations, and control.
  • Advanced modelling and simulation approaches to improve the developments of vehicle functions, including digital-twin techniques and implementations, high-efficiency program framework design under embedded platform.
  • Application cases for ground vehicles (cars, buses, tracked vehicles, and e-bikes, etc.) under structured/ unstructured roads, underwater robots, vessels, aircrafts, and so forth.

Prof. Dr. Yuan Zou
Prof. Dr. Chao Han
Dr. Ningyuan Guo
Dr. Tao Zhang
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. Energies 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 2600 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

  • control algorithms
  • diagnosis
  • electrified vehicles
  • latest technologies
  • estimation
  • fault tolerance
  • modelling
  • V2X techniques

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 7833 KiB  
Article
Modeling and Experiments of a Wireless Power Transfer System Considering Scenarios from In-Wheel-Motor Applications
by Jianyang Zhai, Xudong Zhang, Shiqi Zhao and Yuan Zou
Energies 2023, 16(2), 739; https://doi.org/10.3390/en16020739 - 08 Jan 2023
Viewed by 1772
Abstract
This paper presents the design and modeling procedure of a wireless power transfer (WPT) system applied to In-wheel-motor (IWM). The system is designed to transmit over 10 kW of power following the physical constraints faced by the IWM applications. The issues of coil [...] Read more.
This paper presents the design and modeling procedure of a wireless power transfer (WPT) system applied to In-wheel-motor (IWM). The system is designed to transmit over 10 kW of power following the physical constraints faced by the IWM applications. The issues of coil misalignment and load change are discussed as particular scenarios in IWM. The finite element model is built for circular, rectangular, and double-D coils, finding that the rectangular coil has the best performance considering the transmission interval and misalignment resistance. The circuit design procedure is presented, and the analysis of the influence of load and mutual inductance change on the WPT system is addressed. Finally, the performance of the design is verified with experiments on a full-scale prototype. It is proved that the WPT system successfully transmits 10 kW of power with a DC–DC efficiency of over 90% under a transmission interval of 140 mm. The output voltage is stable under 40 mm coil misalignment scenarios and over 50% load change. Full article
(This article belongs to the Special Issue Advanced Technologies in Electrified Vehicles)
Show Figures

Figure 1

20 pages, 5079 KiB  
Article
High-Precision Fault Detection for Electric Vehicle Battery System Based on Bayesian Optimization SVDD
by Jiong Yang, Fanyong Cheng, Maxwell Duodu, Miao Li and Chao Han
Energies 2022, 15(22), 8331; https://doi.org/10.3390/en15228331 - 08 Nov 2022
Cited by 8 | Viewed by 1832
Abstract
Fault detection of the electric vehicle battery system is vital for safe driving, energy economy, and lifetime extension. This paper proposes a data-driven method to achieve early and accurate battery system fault detection to realize rapid early warning. The method first adopts the [...] Read more.
Fault detection of the electric vehicle battery system is vital for safe driving, energy economy, and lifetime extension. This paper proposes a data-driven method to achieve early and accurate battery system fault detection to realize rapid early warning. The method first adopts the support vector data description model mapping the feature of unlabeled voltage and temperature into a minimum volume hypersphere in high-dimensional space. When the feature is located outside the hypersphere, it is judged to be faulty. Then, to overcome the problem of hyperparameters selection, Bayesian optimization and a small amount of label data are used to iteratively train the model. This step can greatly improve the fault detection ability of the model, which is conducive to mining early and minor faults. Finally, the proposed model is compared with three unsupervised fault detection models, principal component analysis, kernel principal component analysis, and support vector data description to validate the performance of fault detection and robustness, respectively. The experimental results show that: 1. the proposed model has high detection accuracy in all four fault datasets, especially in the highly concealed cumulative short-circuit fault, which is substantially ahead of the other three models; and 2. The proposed model has higher and more stable accuracy than the other three models even in the case of a large range of signal-to-noise ratio. Full article
(This article belongs to the Special Issue Advanced Technologies in Electrified Vehicles)
Show Figures

Figure 1

Back to TopTop