Battery Systems Simulation Engineer #702042

Job Location: Toronto (Ontario)

KEYS ARE: Simulation Electric Automotive Battery – Develop numerical models to predict Lithium-Ion battery performance, degradation, aging, thermal safety, and cell life estimation using electro-chemical physics based and machine learning models. – M.Sc. or Ph.D. degree in Mechanical Engineering, Chemistry, Math, Physics, E. Engineering, Computer Science, or equivalent

Responsible for battery modelling, system simulations, and analysis of vehicle battery cells, battery packs, and the BMS. Develop predictive models using physics-based electrochemistry models and data models for performance and safety. Contribute to the development of battery systems Digital Twin platforms for battery powered electric vehicles.

Responsibilities: (not limited to)

  • Responsible for battery cell and battery pack models and simulations by developing and implementing predictive methods for battery performance and safety under various operating conditions.
  • Develop numerical models to predict Lithium-Ion battery performance, degradation, aging, thermal safety, and cell life estimation using electro-chemical physics based and machine learning models.
  • Develop methodologies for multi-scale coupled physics, electrochemistry, thermal, structural, fluid-structure interaction (FSI), and electromagnetic EMI, to analyse the behaviour of cells, modules, packs, and systems.
  • Develop battery estimation algorithms and models for SOC, SOH, define metrics for performance and usage limitations under definite operating conditions, link battery performance and requirements to the overall system (vehicle) efficiency and create system/component level targets for battery design improvements.
  • Build Reduced Order and Surrogate Models from high fidelity models for embedded real time applications (Digital Twins, BMS) and to run large system models and conduct DOEs. Contribute to the development of battery system Digital Twins for BEV.
  • Perform statistical analysis, UQ, and optimization of battery performance
  • Develop a methodology to estimate geometric and material model parameters for simulation and investigate new potential materials.
  • Responsible for creating, updating, and managing multiple fidelity model libraries related to cells and battery systems.
  • Work with the other battery division teams (design, testing) to define targets and drive design forward.
  • Contribute, as a battery specialist, to vehicle system 1D model integration, coordinating new & updated subsystem models with vehicle model owners, using GT-Suite.
  • Lead battery model calibration activities to validate models. Collaborate with design and test teams to design validation and verification tests based on requirements.
  • Support the development of new concepts sharing and interacting within a multi-disciplinary team.
  • Preparation of concise reports with clear recommendations for stakeholders and customers.

 Knowledge Base (not limited to)

  • Proven experience in applied multi-physics simulations and electrochemistry
  • Experienced in developing data driven based models
  • Fundamental Knowledge of Electrochemistry
  • Ability to apply Multiphysics techniques to a wide array of problems (electrochemical, thermal, structural, flow, magnetics etc.), preferred experience with battery systems
  • Experienced in creating data driven based models for electrochemical/thermal/mechanical systems
  • Knowledge of innovative statistical methods, UQ, machine learning techniques, reduced order, and surrogate models
  • Good programming, mathematical and advanced data processing capabilities (Python, R, Matlab)
  • Understanding of simulation driven design, collaborative sharing, and demonstrated ability of technical communication at different levels (engineers, management)
  • Experience in test design and experimental set up (battery testing equipment preferred)
  • Willingness to learn new tools as necessary
  • Strong written and verbal communication skills

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