According to foreign media reports, electric vehicles are driven by rechargeable lithium ion batteries (LIB), but at present, people have not fully understood and perfected lithium ion batteries. Given that electric vehicles are expected to replace fuel vehicles, any research that can improve the performance of lithium-ion batteries will benefit the development of electric vehicles and improve the environment. Matthias Preindl and Alan West, two professors at Columbia University, are developing a machine learning model that can more accurately estimate the charge level of lithium-ion batteries. At present, it is estimated that the battery charge state still has an error rate of 5%. The model goal developed by the team is to reduce the error rate to 1%. The research was funded by the Seed Data Fund of the Columbia Data Science Institute.
As everyone knows, the battery management system is mainly used to capture the health status of the battery and predict the remaining life of the period. The above two concepts can help electric vehicle owners know when to stop to charge the battery, and when to replace the battery. Then, a model with high estimation accuracy allows the battery management system to identify and protect weak batteries, thereby extending the life of the battery pack.
To design the machine learning model, the team will apply the disturbance signal (a series of current signals generated by power electronic converters) to the lithium-ion battery, which allows the battery to emit a detectable electrical response. The team will test such batteries in the laboratory and use power electronic converters to obtain data from batteries installed on electric vehicles. Such data is generated every minute and can measure battery functions such as battery temperature, voltage and current fluctuations, resulting in hundreds of thousands of data points. Therefore, the team is designing an algorithm to evaluate such data and design an optimization model.
Preindl is an expert on how the battery interacts with external components, and chemical engineer Allen West understands the chemical composition inside the battery. The two of them are combining their engineering knowledge and advanced data science and technology to design a model that can predict how to get the best performance of the current lithium-ion battery.
Preindl said: "In fact, we do not have a quantitative method to understand the behavior of lithium-ion batteries. Once we have quantitative data, we will know when the battery needs to be charged, how long it can be used, when it needs to be replaced, and how to extend Battery life. "
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