Battery Algorithms Engineer

Job Description

As a member of the Vehicle Controls Battery Algorithms group, you will join a small team within the Vehicle Software organization, whose role is to model, develop, specify, and implement control and estimation algorithms for the high voltage battery in Tesla vehicles.

These algorithms cover a wide range of customer facing attributes like state-of-energy, state-of-health, power prediction and management, fast-charging, etc. You will work highly cross-functionally, with engineers across cell development, modeling, durability and qualification, and BMS firmware, integration, and validation teams to advance the state of the art of battery estimation and management algorithms in Tesla vehicles.

Unlike anywhere else in this field, at Tesla, you will get the unique opportunity to work on a vast portfolio of cell technologies, and you will be challenged to develop, implement, and deploy robust algorithms that scale to the largest fleet of EV battery packs in the world.

Job Responsibilities

• Use a variety of cell and battery pack models, fleet data, and laboratory test data to create state-of-the-art feedback control and estimation algorithms for Tesla’s high voltage battery packs
• Own a subset of the algorithms that run on the BMS in millions of Tesla vehicles worldwide – these algorithms span cell capacity, impedance, energy, fast charging, and degradation estimation to diagnostics of sensors, cells and battery pack components
• Research, design, prototype, and prove functionality of novel battery estimation and control approaches to maximally extract performance from our cells
• Create physics-based models of cell and pack elements of the appropriate fidelity to analyze problems; use these models to design estimation and control algorithms
• Prototype and test your algorithms, and work with Firmware Engineers where required to productionize your algorithms in our codebase
• Build fleet data pipelines and tools to monitor performance of your algorithms in our fleet, identify areas for improvement, and test efficacy of proposed solutions
• Work cross-functionally with Cell Modeling, Cell Qualification, Firmware, and Battery Safety organizations to advance state-of-the-art of BMS algorithms at Tesla

Job Requirements

• Degree in Mechanical Engineering, Electrical Engineering, Materials Science, or equivalent in experience and evidence of exceptional ability
• Excellent background in linear systems analysis, state-estimation, and first principles design and analysis of control systems
• Proficiency with analyzing large datasets and algorithm performance in MATLAB/Python
• Excellent understanding of the electrochemical physics of lithium-ion cells, and experience with modeling these physics across a range of fidelities
• Ability to ground-up design, analyze, and implement battery management algorithms in real-world applications, demonstrated by strong examples
• Strong understanding of battery diagnostics and anomaly detection algorithms
• Demonstrated ability to collaborate cross-functionally, work hands-on, and execute on open-ended projects in a fast-paced, resource-constrained environment
• Basic proficiency with embedded software development in C/C++
• Experience productionizing physics model-based fast-charging algorithms, preferred 
• Experience in executing tests on cells in a laboratory environment, preferred