BESS Digital Twin Modelling Engineer

Looking for challenging role? If you really want to make adifference - make it with us 

Siemens Energy is focusedon helping customers navigate the world’s most pressing energy problems.

As a world leader indeveloping and producing the most advanced engineering technologies, we improvelives and further human achievements worldwide, while also protecting theclimate - all thanks to our employees.

Your new role –challenging and future-oriented.

• As the battery modelling and simulation engineer in the BESSdigitalization team, you will develop high-fidelity and system-theoretic models(Digital Twins) that can express the behavior of a cell, module and/or pack inmathematical form. Using modern-day software tools and programming languagessuch Python/R/MATLAB/Simulink, you will be creating models that can simulatethe electrical and thermal performance of a battery cell, module or pack anddefine the tests needed to correlate the models.
• Key Responsibilities:
• Develop system-theoretic models (Digital Twins) at cell, module,or pack level, including an electrical and thermal sub-model usingphysics-based modelling, equivalent circuit, and data-driven techniques.
• Perform electrical performance high and low fidelity simulationsat module and/or pack level such as capacity, energy efficiency, constantpower, discharge power, drive profiles, fast charging etc.
• Perform numerical simulations to identify performance limitations,optimize cell and module/pack design and develop key performance indicators.
• Contribute to the development of digital twins or a portfolio ofbattery models and algorithms, such as open-circuit voltage (OCV) predictionwith hysteresis, state of charge (SOC) tracking, capacity learning over life,estimation of internal cell temperature, lifetime prediction, and state ofhealth (SOH) reporting etc.
• Develop ageing models at module and pack level in coordinationwith the cell team.
• Collaborate with cross-functional teams, including planning andcoordinating tests required for model parameterization and characterization.

         We don’t need superheroes, just superminds:

• Master's or PhD Degree in electro-chemical engineering, advancedcontrol and systems Engineering, Electrical Engineering, Machine learning/AI,Mechanical Engineering, Computer Science, Mathematics.
• Strong understanding of the lithium-ion electrochemistry,system-theoretic principles and mechanical, electrical, and thermal systems ina battery cell/pack/module.
• Familiarity with battery modelling techniques (Black-box, Whiteboxand Grey-box) and the ability to blend physical, empirical, analytical,equivalent circuit, and stochastic models to achieve the desired outputparameter.
• Competence in battery state estimation and control design,including deep insights into battery cell electro-thermal-ageing dynamics andmodelling,
• Experience with modelling lithium-ion cells /packs and modulesincluding Newman model, Randle’s Equivalent Circuits, single-particle models,Kalman filtering/extended Kalman filtering/Particle filtering etc.
• Experience working with Python (PyBAMM or any other modellingframework), R, MATLAB, Simulink/Simscape.
• Demonstrated ability to work in a dynamic and multi-culturalenvironment where initiative and ownership are necessary.
• Nice to Have
• Knowledge of probabilistic machine learning and deep learningframeworks and techniques.
• BMS knowledge
• Experience with CAE battery simulation.
• Experience with algorithm design, implementation, calibration andcode optimization.
• Experience in organizing and carrying out diagnostic tests onbattery packs and modules.