LG Energy Solution and Qualcomm Collaborate on Advanced BMS Diagnostic Solution for Electric Vehicles

March 12, 2024 – LG Energy Solution has announced a collaboration with Qualcomm to develop a cutting-edge Battery Management System (BMS) diagnostic solution for the next generation of electric vehicles, according to recent media reports.

Through this partnership, LG Energy Solution intends to integrate its BMS diagnostic software with specific features of Qualcomm’s Snapdragon Digital Chassis, aiming to create a more advanced BMS offering. LG Energy Solution is widely recognized for its advanced battery technology and consistent performance, maintaining a leading position in the battery technology sector. Meanwhile, Qualcomm, a globally renowned communication technology company, has demonstrated its prowess in wireless communication and chip technology. The collaboration is expected to leverage the respective technical strengths of both companies.

Unlike existing BMS software that runs on low-specification hardware, the new solution will harness the computational capabilities of high-performance Snapdragon System-on-Chips (SoCs). This enhancement results in over 80 times improvement in computing power, enabling the real-time execution of more complex battery algorithms and the implementation of additional advanced BMS functionalities without the need for server communication.

Historically, most battery diagnostic algorithms have relied on predictions rather than extracting data from actual batteries. However, the new BMS technology will combine Qualcomm’s Snapdragon Digital Chassis-specific features with LG Energy Solution’s BMS diagnostic software. This innovative approach allows the system to monitor battery status in real-time, accurately diagnose battery performance, identify and address potential issues promptly, ensuring optimal battery operation and extending its lifespan.

According to LG Energy Solution, this technology is based on cross-analysis of data from 100,000 electric vehicles and direct analysis of over 10,000 batteries exposed to real-world usage conditions, resulting in a unique battery analysis algorithm.


Leave a Reply