Ford Racing Powertrain Simulation Engineer

Ford; Allen Park (MI); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Ford Racing is seeking an engineer to build powertrain plant models and CAE tools supporting racing programs, concept exploration, and calibration development. The role requires developing simulations for a range of propulsion systems and validating them against track data.

You will work with Matlab/Simulink to create vehicle-level models and collaborate across controls, calibration, test, and program teams in a hybrid onsite setting in Allen Park, MI.

Qualifications

• Bachelor-level engineering degree or higher in a relevant field.
• 2+ years modeling dynamic systems for simulation and control.
• 2+ years in real-time control system design and validation.
• Strong understanding of automotive powertrain concepts and vehicle dynamics.
• Proficiency with Matlab/Simulink for modeling,分析 and embedded software.

Responsibilities

• Build powertrain plant models and CAE tools to support decisions for racing programs.
• Size and select powertrain hardware and support hardware-in-the-loop testing.
• Develop models for controls calibration, lap-time prediction, and drive-cycle evaluation.
• Integrate multidisciplinary vehicle models with controls, aerodynamics, and external models.
• Plan hardware testing and parameter estimation to validate models against track data.

Skills

Dynamic system modeling

Real-time control

Automotive powertrains

Matlab/Simulink

Python

C++

Education

Bachelor's degree in Mechanical Engineering, Electrical Engineering, Physics, or equivalent

MS/PhD preferred in related field

Tools

AMESim

GT-POWER

Dymola

CarSim

CarMaker

Job description

Racing is where our story began. In 1901, Henry Ford climbed into a car he built himself-"Sweepstakes"-and beat America's most famous driver. He wasn't a racer, but he had to win. He did. Ford Motor Company was born from that victory.

That fighting spirit lives on in Ford Racing today. We're the engineers, strategists, and competitors who bring Ford's track-tested edge into every vehicle we build. Every track, every stage, every proving ground-that's where we prove ourselves.

The result: one of the world's most iconic brands, legendary nameplates, and a team unmatched in the industry.

Our mantra: Race to win, engineer to lead.

If you're a competitor, innovator, or performance obsessive, Ford Racing is where you belong. Help us write the next chapter.

In this position...

You will build the powertrain plant models and simulation tools that power key decisions across Ford Racing's production and motorsports programs. That means supporting concept exploration for future vehicles, helping program teams size and select powertrain hardware, and providing plant models that enable controls and calibration development, lap time prediction, drive cycle evaluation, and more. This role is hybrid and requires at least 4 days per week onsite in Allen Park, MI.

What you'll do...

Use Matlab/Simulink (and other programs) to develop vehicle, powertrain, and component-level CAE models to analyze dynamic system performance and complex system interactions. Models will span the entire vehicle, including ICE (internal combustion engines), batteries, electric machines, transmissions, driveline, and tires. Manage integration of powertrain plant models with other multidisciplinary models - including vehicle dynamics, aerodynamics, vehicle controls, and external partner models - to create cohesive simulation environments. Model applications include desktop simulation, model-in-the-loop, software-in-the-loop, hardware-in-the-loop, and driver-in-the-loop testing to develop controls and calibrations for future and existing racing and road vehicles. Work cross-functionally with controls, calibration, test, and program engineers. Design and perform concept vehicle simulation studies to develop hardware and vehicle requirements recommendations for program and systems engineering teams. Design and implement plant models with sufficient fidelity to support controls and calibration development. Use driver and car feedback to develop driver-in-the-loop and dyno control plant models that replicate behaviors observed from track driving. Design models and tools to optimize powertrain hardware and control parameters to meet targets. Plan and perform hardware testing using test vehicles, dynamometers, labs, or external supplier services to develop, parameterize, and validate plant models. Develop analytical data processing software tools to estimate and optimize model parameters to improve and maintain the correlation between models and development hardware. Deploy trackside tools to analyze on-track powertrain performance and identify performance deltas relative to the model. Utilize machine learning, AI, and optimization techniques to characterize complex systems and reduce model calibration effort.

You'll have...

• Bachelor's degree in Mechanical Engineering, Electrical Engineering, Physics, or an equivalent technical degree.
• 2 years' experience developing dynamic system models for simulation and control design.
• 2 years' experience in the design, development, and validation of real-time control systems in both modeling environments and prototype hardware.
• Understanding of automotive powertrain (including conventional, hybrid electric vehicle, and battery electric vehicle) systems and controls, general physics, thermos and fluid dynamics, heat transfer, and vehicle dynamics, with fundamental knowledge of general dynamics, hydraulics, electric machines, batteries, internal combustion engines, and mechatronic actuators.
• 2 years of demonstrated experience using Matlab/Simulink for system modeling, simulation, data analysis, and embedded control software implementation.

Even better, you may have...

• M.S. or Ph.D. in Mechanical, Aerospace, or Electrical Engineering, or a similar field, with emphasis on simulation, combustion engines, or control system design.
• Deep knowledge of combustion engine operation to assist with high-fidelity engine simulation plant model development and correlation to test data.
• Experience integrating multidisciplinary vehicle subsystem models into simulation environments.
• Experience using industry-standard modeling and simulation packages such as AMESim, GT-POWER, Dymola, CarSim, CarMaker, etc. Experience with Python and C++. Experience with racing tools, telemetry systems, and vehicle dynamics software.
• Experience implementing AI-based and machine learning engineering solutions or developing advanced analytical tools (i.e., random forest regressor, neural network, model-based calibration, parameter optimization and estimation,