Battery Pack Simulation Engineer M/F

As a Senior Battery Pack System Simulation Engineer, you are responsible for developing and maintaining system-level battery pack models to support battery pack development across all applications, including automotive.

You build and integrate surrogate/reduced-order models in close collaboration with the CAE engineers covering electrical, electrochemical, thermal, mechanical, durability, control, safety, and optimization aspects of battery pack systems.

You own your surrogate/equivalent-circuit/reduced-order model requirements and the associated parameter identification and validation workflows, in close collaboration with the CAE engineers and with support from BMS, testing, and validation engineers.

You provide simulation-based insight to support architecture trade-offs, control development, performance prediction, lifetime assessment, and safety-oriented engineering decisions.

This role is part of the CAE & Advanced Methods Group and supports the Battery Pack and System Group with system-level simulation evidence for pack architecture justification, optimization, root-cause analysis, and with control-oriented simulations for BMS/BTMS calibration, validation, robustness and verification.

Main responsibilities

• System-Level Battery Pack Model development & Simulation
  • Develop and maintain multi-domain battery pack models representing electrical, electrochemical and thermal behaviors as well as pack durability, swelling and cooling loop operation and control.
  • Define the appropriate model fidelity and simulation approach depending on project phase, use case, and required decision timeline.
  • Develop and operate workflows for trade‑off studies, sensitivity analysis, design of experiments, surrogate model generation, and multi‑objective optimization (safety constraints, integration constraints, mass, and cost‑related drivers, …).
  • Assess implication of control strategy and BMS/BTMS algorithms on system operation and fault scenarios (MiL, SiL).
  • Run simulations for normal (usage profiles, testing, thermal) and fault conditions, including cooling loss scenarios, sensor failures or drift, electrical fault conditions, thermal excursions, and safety‑relevant operational limit studies.
  • Model and workflow standardization, automation and documentation.
• Empirical & EC-Type Model Requirements, Development & Parameter Identification
  • Establish and own model requirements for equivalent circuit, thermal, ML, and other empirical/surrogate/reduced‑order battery models for system simulation and control‑oriented applications under normal and fault scenarios.
  • Support CAE engineers for the development, maintenance, and deployment of ECM/ROM/ML/surrogate models.
  • Coordinate model parameter identification with CAE, testing, and product validation engineers at the cell, module, and pack levels, including OCV and DCIR/ACIR, SOC/temperature dependencies, and aging‑related parameter evolution.
  • Maintain model assumptions and limitations, parameter traceability, model‑change traceability, validation status, applicability domain, and release and usage guidelines.
• Multi‑Physics Model Integration
  • Integrate domain knowledge into the battery pack system models and translate high‑fidelity simulation inputs into fast and decision‑oriented system models in close collaboration with CAE engineers.
  • Develop co‑simulation workflows with integrated high‑fidelity models through direct coupling or using FMI/FMUs.
• BMS/BTMS Algorithm Development & Control‑Oriented Support
  • Develop advanced state estimation (SOC, SOH, SOX) algorithms, including KF, MHE, physics‑based, and machine‑learning approaches and incorporate/execute in system simulation workflows.
  • Evaluate/recommend voltage/current/temperature limits, derating strategies, balancing impact, temperature non‑uniformity, cooling system operation limits and constraints, sensor sensitivity, etc.
  • Contribute to Verkor's IP portfolio.
  • Provide simulation support to the BMS development engineer for model‑based verification and validation, including estimator robustness and calibration, MiL, SiL and HiL test bench.

Requirements

• Master's degree (Bac+5) or PhD in Electrical Engineering, Systems Engineering, Control Engineering, Mechanical Engineering, or equivalent.
• Specialized knowledge in system control design and state estimation algorithms (KF, MHE, ML, empirical, …), Li‑ion battery cells and packs, BMS and BTMS, MiL, SiL.
• 5 years of experience minimum in battery or other electrified system simulation (automotive OEMs/Tier 1 suppliers preferred), including state estimation and control, with demonstrated technical track record and model development/maintenance ownership.
• Proficiency in system simulation tools (Simulink, Simscape/Modelica, Ansys Twin Builder, Amesim, …) and scientific coding (Python, Matlab).
• Experience in surrogate and reduced‑order modelling, including model building, calibration, and validation.
• Experience in multi‑domain system model integration and model‑based system design.
• Experience in multi‑objective optimization (trade‑offs, pareto front, etc.), statistical analysis (error propagation, uncertainty quantification, robustness, etc.), and other study scenarios.
• Familiar with electrochemical engineering, battery chemistries (NMC, LFP, …), thermal engineering, and battery durability.
• Familiar with battery safety and system fault scenarios.
• Proficiency in English / French is a plus.