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Battery Thermal Management of Electric Vehicles: An Optimal Control Approach

[+] Author Affiliations
Yasaman Masoudi, Ahmad Mozaffari, Nasser L. Azad

University of Waterloo, Waterloo, ON, Canada

Paper No. DSCC2015-9723, pp. V001T13A003; 7 pages
  • ASME 2015 Dynamic Systems and Control Conference
  • Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
  • Columbus, Ohio, USA, October 28–30, 2015
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5724-3
  • Copyright © 2015 by ASME


The main goal of the current investigation is to evaluate the potential of the optimal control techniques to improve the quality of battery thermal management (BTM) in electric vehicles (EVs). The BTM is of profound importance in EVs, where battery is the sole power source and any unexpected change in the battery temperature could dramatically affect the vehicle performance and its driving range. As a result, the battery temperature should be maintained within a specific range to lead to the best vehicle performance. Despite the obvious importance of this issue, there exist rare reports in the literature addressing the design of optimal controllers for BTM of EVs. Here, the authors intend to apply and compare two controllers to solve this problem for an EV: an optimal controller designed upon dynamic programming (DP) and a proportional integral-derivative (PID) controller. The results indicate that by using DP, a less amount of the battery power will be demanded, and therefore, the vehicle’s driving range can be increased.

Copyright © 2015 by ASME



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