The inevitable battery degradation poses significant challenges to the accurate estimation of the state-of-charge (SoC), a key battery state that reflects the remaining driving distance of electric vehicles. We here develop an estimator that is robust to battery ageing. First, a set of random models is drawn upon an accurate base model. Then, SoC estimations are carried out on these random models with light-weight gain-switching observers. Finally, the outputs of the gain-switching observers are fused to generate accurate SoC values. The proposed solution is experimentally verified, exhibiting 2% estimation accuracy for batteries with different ageing degrees.
|Number of pages||4|
|Publication status||Published - 2021|
|Event||The 4th International Conference on Electrical Intelligent Vehicles - Nanjing, Jiangsu, China|
Duration: 25 Jun 2021 → 28 Jun 2021
|Conference||The 4th International Conference on Electrical Intelligent Vehicles|
|Period||25/06/21 → 28/06/21|
Bibliographical noteThis work was supported in part by the Ministry of Science and Technology of People's Republic of China (SQ2019YFB170029), Guangdong scientific and technological project (2017B010120002), Hong Kong Research Grants Council CERG project (16208520), and the Shenzhen-Hong Kong Innovation Circle Category D Project: SGDX 2019081623240948.
- Electric Vehicles
- State of Charge
- State Observer
- Battery Management System