Modeling and adaptive control for supercapacitor in automotive applications based on artificial neural networks

•Comprehensive approach to modeling supercapacitors used in hybrid vehicles using ANN.•Discover supercapacitor module structure with hierarchical multilevel approach.•The model was applied to control the supercapacitor voltage.•Accuracy of the neural model and controller are confirmed with validation tests.•Accurate tools for SC monitoring and control suitable in energy management systems.

The behavior of a supercapacitor is a complex and nonlinear function of its current rate, temperature, chemistry and history, and hence cannot easily be determined. In this study, we use a one-layer feed-forward artificial neural network (ANN), trained using the back-propagation algorithm, to model the behavior of supercapacitors used in automotive applications. Possible improvements of the neural network model using a multilevel approach are discussed. Then, on the basis of this model, a neural controller is developed in order to control the supercapacitor voltage. Simulation results confirmed the accuracy of the model compared to measurements from supercapacitor module power-cycling.