Data and Code for Manuscript Titled "Optimal Sizing of Hybrid High-Energy/High-Power Battery Energy Storage Systems to Improve Battery Cycle Life and Charging Power in Electric Vehicle Applications"
Published: 21 March 2022| Version 1 | DOI: 10.17632/k7jpvv33sm.1
Contributors:
Farshid Naseri, , Turev SarikurtDescription
The research data is associated with the article entitled "Optimal Sizing of Hybrid High-Energy/High-Power Battery Energy Storage Systems to Improve Battery Cycle Life and Charging Power in Electric Vehicle Applications". It includes the hybrid battery model including performance and lifetime modes as well as energy management. Likewise, MATLAB m-files for optimal sizing by the genetic algorithm are included in the dataset. The folder titled "Drive cycle data" includes speed and power data of the Mitsubishi i-MiEV over NEDC and WLTP (class 3) driving cycles.
Files
Steps to reproduce
Follow flowcharts represented in Fig. 1 and Fig. 10 to understand how to consider different design targets in the optimal sizing problem.
Institutions
Aarhus Universitet Faculty of Technical Sciences
Categories
Genetic Algorithm, Hybrid Energy System