The Scientific World Journal

Modeling, Control, and Optimization Technologies in Electric Drive Vehicles


Status
Published

Lead Editor

1Beijing institute of Technology, Beijing, China

2University of Southampton, Southampton, UK

3Beijing Jiaotong University, Beijing, China

4Kettering University, Flint, USA


Modeling, Control, and Optimization Technologies in Electric Drive Vehicles

Description

To address the two urgent issues nowadays of protecting the environment and achieving energy sustainability, it is of strategic importance on a global scale to replace oil-dependent vehicles with electric drive vehicles (EDVs). Numerical simulation and optimization are essential to simulate the actual hardware and minimize the development. Accurate and efficient modeling, control, and optimization technologies are indispensable tools.

This special issue invites articles on the state-of-the-art developments for modeling, control, and optimization approach of EDVs. This special issue covers circuits, components, and system-level modeling method for energy storage, power electronics, and electromechanical energy convertors in EDVs. Additionally, the articles on economic aspects for promoting the market penetration of EDVs are also welcome. We sincerely solicit original high-quality technical papers that are not under consideration by other publications.

Potential topics include, but are not limited to:

  • Systematic control and power management: system-level modeling, control, optimization, diagnostics, prognostics, reliability, power management, and health management technologies for electric vehicles
  • Energy systems: component, circuit, and system-level modeling, estimation and optimization method for energy storage systems, including battery, fuel cell, ultracapacitor, and hybrid energy storage system, and design, control, and optimization of battery management system
  • Batteries and grouping technology: advanced battery materials, battery degradation and mechanism, battery grouping technology, battery optimal charging method, cycling life’s prediction, and thermal modeling and management
  • Traction motor system: electric motor, electric motor controller, regenerative braking, control strategy, and experiment technology
  • Electric auxiliary parts: electric power steering, electric steering, electric braking, low-voltage DC/DC, and electric air conditioner

Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 730347
  • - Editorial

Modeling, Control, and Optimization Technologies in Electric Drive Vehicles

Hongwen He | Suleiman M. Sharkh | ... | Rui Xiong
  • Special Issue
  • - Volume 2015
  • - Article ID 302867
  • - Research Article

Conventional, Hybrid, or Electric Vehicles: Which Technology for an Urban Distribution Centre?

Philippe Lebeau | Cedric De Cauwer | ... | Thierry Coosemans
  • Special Issue
  • - Volume 2015
  • - Article ID 979321
  • - Research Article

Analysis of Ageing Effect on Li-Polymer Batteries

Simone Barcellona | Morris Brenna | ... | Luigi Piegari
  • Special Issue
  • - Volume 2015
  • - Article ID 584075
  • - Research Article

Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

Jiankun Peng | Hongwen He | ... | Hongqiang Guo
  • Special Issue
  • - Volume 2015
  • - Article ID 363094
  • - Research Article

A Novel Range-Extended Strategy for Fuel Cell/Battery Electric Vehicles

Jenn-Jiang Hwang | Jia-Sheng Hu | Chih-Hong Lin
  • Special Issue
  • - Volume 2015
  • - Article ID 354952
  • - Research Article

Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization

Liyong Niu | Di Zhang
  • Special Issue
  • - Volume 2014
  • - Article ID 261085
  • - Research Article

A Traction Control Strategy with an Efficiency Model in a Distributed Driving Electric Vehicle

Cheng Lin | Xingqun Cheng
  • Special Issue
  • - Volume 2014
  • - Article ID 958239
  • - Research Article

Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System

Shuo Zhang | Chengning Zhang | ... | Qinghui Wang
The Scientific World Journal
 Journal metrics
Acceptance rate23%
Submission to final decision57 days
Acceptance to publication59 days
CiteScore1.430
Impact Factor-
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