Battery State of Charge Workflow

Battery state of charge (SOC) is the level of charge of an electric battery relative to its capacity measured as a percentage. SOC is critical information for the vehicle energy management system and must be accurately estimated to ensure reliable and affordable electrified vehicles (xEV). However, due to the nonlinear temperature, health, and SOC dependent behavior of Li-ion batteries, SOC estimation is still a significant automotive engineering challenge. Traditional approaches to this problem, such as electrochemical models, usually require precise parameters and knowledge of the battery composition as well as its physical response. In contrast, using neural networks is a data-driven approach that requires minimal knowledge of the battery or its nonlinear behavior [1].

This example workflow demonstrates the steps for training a network for estimating battery SOC, compressing the network, and using the network in Simulink^®.

1. Predict Battery State of Charge Using Deep Learning

2. Compress Network for Estimating Battery State of Charge

3. Battery State of Charge Estimation in Simulink Using Deep Learning Network

References

[1] Kollmeyer, Phillip, Carlos Vidal, Mina Naguib, and Michael Skells. “LG 18650HG2 Li-Ion Battery Data and Example Deep Neural Network XEV SOC Estimator Script.” Mendeley, March 5, 2020. https://doi.org/10.17632/CP3473X7XV.3.

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