Battery Electric Vehicles: A Study on State of Charge and Cost-Effective Solutions for Addressing Range Anxiety
While Battery Electric Vehicles (BEVs) offer environmental benefits by reducing carbon emissions during use, their range remains limited compared to conventionally fuelled vehicles. This paper focuses on identifying factors that directly influence BEV range and explores strategies to mitigate range anxiety among potential users. Specifically, it reviews the impact of battery cell characteristics and vehicle lightweighting. Using the WLTP Class 3B drive cycle, energy consumption and Depth of Discharge (DoD) were evaluated across various battery capacities. Multiple Lithium-Ion battery models were simulated to analyse discharge behaviour, while vehicle mass composition was examined to assess the effectiveness of lightweighting in extending driving range. A lower initial State of Charge (SoC) and a standard discharge rate were used to estimate the remaining range, highlighting an approximate gain of up to 6 km at lower DoD levels. This work aims to accurately demonstrate how battery technology and structural weight impact energy consumption and usable range in BEVs. Current modelling approaches often overlook the relationship between driver discomfort and battery performance metrics. The main contribution is to address the gap by integrating Li-ion discharge modelling with vehicle dynamics to estimate range and compare cell characteristics. The ultimate goal is to support cost-effective strategies for increasing BEV usability, aligning them more closely with conventional vehicle expectations and enhancing journey flexibility.
Authors
- Jason Pollock
- Manu Ramegowda (ORCID: https://orcid.org/0000-0002-1331-854X)
- Nashwan Dawood (ORCID: https://orcid.org/0000-0002-4873-7576)
- Foad Faraji (ORCID: https://orcid.org/0000-0002-2559-666X)
- Perk Lin Chong (ORCID: https://orcid.org/0000-0002-1165-6182)
- Zhonglan Hou (ORCID: https://orcid.org/0000-0001-9172-2604)
- Hossein Habibi (ORCID: https://orcid.org/0000-0003-2772-7480)
- Pengyan Guo
Institutions
- North China University of Water Resources and Electric Power (CN)
- Teesside University (GB)
Publication Details
- Journal
- Machines
- Published
- 2025-05-14
- DOI
- https://doi.org/10.3390/machines13050411
- Citations
- 1
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.68
Funders
- Teesside University