Performance Assessment of Two-Wheeler Electric Vehicle Batteries Using Multi-Mode Drive Cycles

• Published in: World electric vehicle journal Vol. 15; no. 4; p. 145
• Main Authors: Lakshmanan, Padmavathi, Abhishek, Anand, Verma, Brijendra Kumar, Ram, Subhash Kumar
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2024
• Subjects: Algorithms; Battery cycles; battery performance assessment; Behavior; drive cycles; Driving ability; Electric vehicles; Energy consumption; Lithium; Performance assessment; Power consumption; Powertrain; R&D; Research & development; Roads & highways; Temperature; two-wheeler EV; user driving behaviour; Velocity
• ISSN: 2032-6653; 2032-6653
• DOI: 10.3390/wevj15040145

This article presents a model-based approach to assess the battery performance of a two-wheeler EV drive train system for various user driving patterns using the selected urban drive cycles. The battery pack is one of the most expensive parts of an EV, and its life is heavily dependent on its usage pattern. The impact of the user’s driving behaviour on the performance parameters of the EV battery pack needs to be investigated. Thus, a two-wheeler EV drive train model was developed in MATLAB with a 5 kW motor, a 4.32 kWh battery, vehicle dynamics, and the power train control algorithms for in-depth analysis of battery performance. The validity of the developed model was tested against various state-of-the-art drive cycles for a duration of 3600 s. Numerous user driving behaviours, such as aggressive, moderate, and slow driving behaviours, were modelled with modified drive cycles, which were used to assess the two-wheeler battery pack performance. An optimum speed range, which ranges from 21 km/h to 34 km/h for different drive cycles, was identified, and these speed ranges minimised the battery energy consumption for the selected drive cycles with the modified drive cycle models.