Title :
Maximizing lithium ion vehicle battery life through optimized partial charging
Author :
Hoke, Anderson ; Brissette, A. ; Maksimovic, Dragan ; Kelly, Denis ; Pratt, A. ; Boundy, David
Author_Institution :
Electr., Comput., & Energy Eng., Univ. of Colorado, Boulder, CO, USA
Abstract :
The limited lifetime, high cost, and large size of current lithium ion batteries are some of the primary obstacles to wider adoption of electric vehicles and plug-in hybrid electric vehicles. Simulations presented in this paper predict that Li-ion battery life can be extended through intelligent charging, especially when predictions of next-day energy needs are used to charge the battery only as needed. As-needed charging minimizes battery degradation by minimizing time spent at high state-of-charge. Preliminary results presented here indicate that the battery of a vehicle used for daily commuting and short errands could see its useable life extended by up to 150 % over unoptimized charging.
Keywords :
battery powered vehicles; hybrid electric vehicles; lithium; secondary cells; Li; battery degradation; electric vehicles; high state-of-charge; lithium ion vehicle battery life maximization; optimized partial charging; plug-in hybrid electric vehicles; Batteries; Degradation; Mathematical model; Resistance; Sun; System-on-chip; Vehicles; Batteries Electric vehicles; Machine learning algorithms; Numerical simulation; Optimization;
Conference_Titel :
Innovative Smart Grid Technologies (ISGT), 2013 IEEE PES
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4673-4894-2
Electronic_ISBN :
978-1-4673-4895-9
DOI :
10.1109/ISGT.2013.6497818