State of health estimation for lithium-ion battery based on multi-stage feature optimization and improved grey wolf optimizer for back propagation neural network
Key Points
Health estimation accuracy improved using feature optimization and grey wolf optimizer.
56% enhancement in prediction accuracy observed with optimized neural network techniques.
Assessment involves advanced neural network methods for more precise health evaluations.
Utilizing improved algorithms may enable enhanced reliability of lithium-ion batteries.
State of health estimation for lithium-ion battery based on multi-stage feature optimization and improved grey wolf optimizer for back propagation neural network | Synapse