Client Overview
One of the leading EV (electric vehicle) manufacturers had been experiencing recurrent problems with its Battery Management System (BMS), such as inappropriate state-of-charge estimations, unequal cell balancing, and regular battery degradation upon application in high-load scenarios. These inefficiencies affected customer satisfaction, warranty claims, and untrustworthy real-world range estimations.
eInnosys worked with the client on the development of their embedded BMS software, where the smart battery estimation strategies, temperature-dependent balancing, and sensor communication in real-time were carried out. This increased battery lifespan by 35%, range estimation by 30% and a phenomenal decrease in battery faults reported in the field.
About the Company
Key Challenges
Bad Battery Health Estimation (SoH)
The system lacked the capability to monitor the degradation of the battery in an accurate manner, leading to poor aging profiles.
Lack of even Cell Discharge and Thermal Imbalance
The balancing logic did not factor in the temperature of the cell and the history of usage, causing certain individual cells to wear out faster.
Irregular Range Reporting
Drivers also had dynamic or inaccurate range estimations even when the battery was fully charged, decreasing confidence in the reliability of EVs.
Inflexible BMS Logic with Limited Update Capability
Lack of such a feature as remote firmware update also implied that optimization could only be performed manually, in the service centre.
Our Embedded Solutions
Adaptive Battery Estimation Algorithms
Kalman Filtering with Coulomb Counting and Open Circuit Voltage (OCV) analysis was adopted by us to enhance the SoC (State of Charge) and SoH (State of Health) accuracy under variable loads.
Firmware Smart Cell Balancing
Developed an adaptive balancing algorithm that considered real-time thermal information, voltage difference, and discharge profiles to balance the cell life.
Real-Time Control with Custom BMS Firmware
We have ported real-time firmware to STM32 and TI C2000 MCUs to bring high-frequency voltage, current, and temperature sensor data over the CAN bus and provide comprehensive battery diagnostics.
Telemetry Integration & OTA Updates
Provided remote diagnostics features and the ability to upgrade the firmware over the air, meaning that the distributed vehicles could be provided with firmware updates securely, without recall.
Tech Stack
Microcontrollers : STM32, TI C2000
Languages : Embedded C, Python (testing automation)
Protocols : CAN bus, LIN, Modbus
Battery Algorithms : Kalman Filter, Coulomb Counting, Open Circuit Voltage
Testing Tools : CANalyzer, Battery Cyclers, LabView
Business Impact
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