Battery System Computational Modelling and

**Looking for challenging role? If you really want to make a difference - make it with us**

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

As a world leader in developing and producing the most advanced engineering technologies, we improve lives and further human achievements worldwide, while also protecting the climate - all thanks to our employees.

**Your new role - challenging and future-oriented**

Due to their high versatility and decreasing costs, Battery Energy Storage Systems (BESS) are becoming a significant technology in transforming electric networks. With energy ratings touching up to several hundreds of MWh, these large BESS generate massive data via many control layers and sensors spread all over the BESS systems. These sensors measure various parameters, from electrical to thermal ones and parameters for self-diagnosis of the system's sub-components and control laws. However, converting this large amount of data into useful information is challenging to get a synthetic yet comprehensive picture of BESS's health and operational behavior. In this context, Siemens Energy R&D is building capabilities to exploit these BESS through the analysis of the operational data with the objectives to check the level of safety of the assets, anticipate the maintenance needs, follow the performance, and eventually extend the lifetime of the projects.

**Responsibilities**:

- Perform Multiphysics simulations (3D), thermal runaway simulations, thermal management assessment, and safety models to predict thermal runaway incidents, thermal design Optimization and correlations using physics-based modelling, hybrid, and data-driven techniques.
- Lead the development of capacity prediction software for lithium-ion cells with SEI, LAM, particle cracking, and Lithium plating degradation models and parameter estimation techniques in PyBAMM, Julia and Python.
- Providing modelling guidance for electro-thermal and electrochemical simulations for battery cells/packs from conceptual design through detailed 3D Multiphysics simulations.
- Perform electrical performance and numerical simulations at module and/or pack level, such as capacity, energy efficiency, constant power, discharge power, drive profiles, fast charging etc., to identify performance limitations and optimize cell and module/pack design.
- Contribute to the development of models and algorithms, such as open-circuit voltage (OCV) prediction with hysteresis, capacity learning over life, estimation of internal cell temperature, lifetime prediction, and state of health (SOH) reporting, ageing models at module and pack level.
- Utilize electrochemical impedance spectroscopy for the state of health assessment.
- Propose new design strategies for anode/cathode and new materials to enhance the capacity of Li-ion cells and validate them through simulations and experimental data.
- Perform charge-discharge cycling data analysis to study capacity fade, capacity utilization etc.
- Identifying root causes of Li-ion battery cell/pack aging or failure from test and proposing strategies on enhancing battery power and extending battery life.
- Perform postmortem analysis of Li-ion cells.

**The other tasks include**:

- Collaborating with test and product engineers to evaluate and optimize test procedures, i.e. HPPC, OCV, thermal and calendar/cycling life tests, and design Li-ion cells/packs to meet desired performance requirements.
- Managing technical meetings and drafting and presenting reports.
- Collaborate with cross-functional teams, including planning and coordinating tests required for model parameterization and characterization.
- Work with the battery energy storage system (BESS) stakeholders to identify the improvement areas in the currently available techniques.

**We don’t need superheroes, just super minds**
- BS/BE/BTech degree in chemical engineering/material science /Electrical engineering. A Master’s or PhD in chemical engineering/material science /Electrical engineering is preferred.
- Proficiency in Multiphysics simulation, Computational modelling, and data analysis, with significant hands-on experience, is expected.
- You should be able to work as an individual contributor (IC role).
- You must have a customer focus and effective stakeholder management skills.
- Knowledge of Li-ion battery electrochemistry, heat transfer, Design of Experiment (DOE), Parameter Optimization,
- Knowledge of data wrangling, data cleaning and data visualization techniques.
- Knowledge of simulation software like PyBAMM, Ansys, Ansys Fluent, COMSOL, Star-CCM+ etc. is desirable.
- Programming skills in Python/R/MATLAB/Simulink etc., and demonstrable skills in standard data visualization libraries like matplotlib, seaborn, bokeh, plotly, ggplot2 etc.
- Creativity and analytical mindset
- Quick learner and detailed oriented
- Excellent communication skills with an ability to present articulated solutions to senior manage