Ball, Andrew

A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles

Wang, Z., Feng, G., Zhen, D., Gu, F., & Ball, A. (2021) · Energy Reports

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 441

A COMPARATIVE STUDY OF ACOUSTIC AND VIBRATION SIGNALS IN DETECTION OF GEAR FAILURES USING WIGNER–VILLE DISTRIBUTION

BAYDAR, N., & BALL, A. (2001) · Mechanical Systems and Signal Processing

Machine Fault Diagnosis TechniquesGear and Bearing Dynamics Analysis

Cited by 323

A review on rapid state of health estimation of lithium-ion batteries in electric vehicles

Wang, Z., Zhao, X., Fu, L., Zhen, D., Gu, F., & Ball, A. D. (2023) · Sustainable Energy Technologies and Assessments

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 107

Adaptable capacity estimation of lithium-ion battery based on short-duration random constant-current charging voltages and convolutional neural networks

Wang, Z., Zhao, X., Zhen, D., Pombo, J., Yang, W., Gu, F., & Ball, A. (2024) · Energy

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 27

State-of-health estimation of lithium-ion batteries using a kernel support vector machine tuned by a new nonlinear gray wolf algorithm

Liu, S., Fang, L., Zhao, X., Wang, S., Hu, C., Gu, F., & Ball, A. (2024) · Journal of Energy Storage

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 18

Predictive control strategies used to solve challenges related to modern railway vehicles

Ngigi, R. W., Pislaru, C., Ball, A., Gu, F., & Anyakwo, A. (2011) · 5th IET Conference on Railway Condition Monitoring and Non-Destructive Testing (RCM 2011)

Railway Engineering and DynamicsVehicle Dynamics and Control Systems

Cited by 5