Battery Cell Model Engineer (SoX Algorithms)

Ultraviolette Automotive Pvt Ltd; Bengaluru Urban; On-site; INR 700,000 - 1,200,000; Full time

Job summary

Ultraviolette Automotive Pvt Ltd is seeking a Battery Cell Model Engineer to design, implement, and validate algorithms for advanced Battery Management Systems. The role focuses on developing SoX frameworks (SOC, SOH, SOP) that ensure the performance and longevity of lithium-ion batteries. Candidates should have deep knowledge of lithium-ion degradation and experience in translating physical phenomena into mathematical models.

This position involves algorithm development, testing protocols, and collaboration for software integration. Knowledge of C/C++ and testing methodologies is required.

Qualifications

• Deep understanding of lithium-ion degradation mechanisms.
• Ability to translate complex physical phenomena into mathematical models.
• Experience with Model-in-the-Loop (MIL) and Hardware-in-the-Loop (HIL) testing.

Responsibilities

• Develop and implement SOC, SOH, SOP algorithms.
• Define and oversee cell-level testing protocols.
• Translate models into production-ready code.

Skills

State of Charge (SOC) estimation algorithms

State of Health (SOH) estimation algorithms

State of Power (SOP) estimation algorithms

Kalman Filters

Recursive Least Squares (RLS)

Machine Learning

Education

Degree in Engineering or related field

Tools

C/C++

Simulink

Job description

Ultraviolette Automotive Private Limited | Full time

Battery Cell Model Engineer (SoX Algorithms)

We are seeking a Cell Model Engineer to design, implement, and validate advanced Battery Management System (BMS) algorithms. You will focus on developing SoX frameworks (SOC, SOH, SOP, SOE) that ensure the safety, longevity, and performance of lithium-ion battery packs. This role requires a deep understanding of lithium-ion degradation mechanisms and the ability to translate complex physical phenomena into robust mathematical models.

Key Responsibilities

Algorithm & Model Development

• Develop and implement State of Charge (SOC), State of Health (SOH), and State of Power (SOP) estimation algorithms.
• Design Equivalent Circuit Models (ECM) or Physics-Based Models (PBM) to represent cell dynamics.
• Utilize advanced estimation techniques such as Kalman Filters (EKF, UKF), Recursive Least Squares (RLS), or Machine Learning-based approaches for time-series battery data.

Characterization & Testing

• Define and oversee cell-level testing protocols (HPPC, Capacity Fade, Cycle Life) to parameterize models.
• Analyze large datasets from battery cyclers to extract electrochemical parameters and aging trends.
• Correlate lab-based data with real-world "field" performance to improve model accuracy.

Software Integration & Validation

• Translate models into production-ready code (C/C++ or auto-generated code from Simulink).
• Perform Model-in-the-Loop (MIL) and Hardware-in-the-Loop (HIL) testing to validate algorithm robustness across various temperatures and aging states.
• Collaborate with BMS software teams to optimize algorithms for real-time execution on low-power microcontrollers.