In an exciting development for the electric vehicle (EV) industry, researchers have unveiled a cutting-edge method for estimating the state of health (SOH) of power battery packs, a crucial factor in ensuring charging safety. This innovative approach, led by a team of experts including LI Chunxi and his colleagues from various prestigious institutions, including Shanghai Maritime University and Hangzhou Dianzi University, promises to enhance the reliability of EVs, which is particularly relevant as the maritime sector increasingly looks to integrate electric technologies.
The research, published in the Journal of Shanghai Jiaotong University, dives into the complexities of battery health, highlighting that factors like battery type, environmental conditions, and user behavior can significantly impact performance. The team tackled the limitations of existing SOH estimation methods, which often rely on data from a limited number of battery cells and lack real-time accuracy.
To overcome these challenges, the researchers introduced a novel estimation method that combines an empirical battery degradation model with a Broad Learning System (BLS) optimized by a Radial Basis Function (RBF). This multi-faceted approach not only provides an initial SOH value from historical charging data but also refines it using real-time data, resulting in a more precise estimate. As LI Chunxi noted, “The estimation error can be trained by the RBF-BLS neural network and real-time charging data, allowing for a higher precise SOH value.”
For the maritime industry, which is increasingly adopting electric propulsion systems and battery technologies, this research holds significant potential. Enhanced SOH estimation can lead to safer and more efficient charging processes for electric vessels, reducing the risk of battery failures while at sea. This could translate into lower operational costs and improved reliability for shipping companies looking to transition to greener technologies.
Furthermore, as the maritime sector faces pressure to reduce carbon emissions, the ability to accurately monitor battery health will be crucial for optimizing the performance of electric ships. This could open up new commercial opportunities for companies specializing in battery management systems and charging infrastructure, aligning with global sustainability goals.
In summary, the findings from LI Chunxi and his team not only advance our understanding of battery health estimation but also pave the way for safer and more reliable electric travel, benefitting both the EV and maritime industries. The research, published in the Journal of Shanghai Jiaotong University, underscores the importance of integrating advanced technologies to meet the challenges of modern transportation.
