Vehicle Controls Engineer - Propulsion Controls

Ford Ford · Auto · Dearborn, MI +1 · Research and Advance Engineering

This role develops advanced vehicle control algorithms for next-generation powertrain systems, focusing on performance, operation, and feel. It involves end-to-end development, including control architecture, simulation, and software implementation. The role also supports platform tools, leverages CAE models, defines testing, provides controls support, documents processes, and researches advanced controls applications. It leverages connected vehicle technologies, including AI/ML techniques, to enhance customer experience and prognostics.

What you'd actually do

  1. Develop vehicle control algorithms for advanced powertrain systems to deliver vehicle attributes, including control architecture selection, algorithm simulation, implementation, and verification and validation via leveraging a combination of model-in-the-loop (MIL), software-in-the-loop (SIL), hardware-in-the-loop (HIL) and vehicle test environments
  2. Support controls team with creation, maintenance, troubleshooting of development of platform tools: software build system, software version and calibration management, data repository management, context-specific AI tools
  3. Leverage, subsystem- and component-level CAE models to analyze dynamic systems and complex system interactions, and to support concept analysis and verification, parameter optimization, and controls/design verification and validation
  4. Define and review physical system testing and characterization to validate CAE models and guide vehicle and control system design
  5. Provide controls and software support to Systems Engineering and Functional Safety work partners

Skills

Required

  • dynamic systems modeling
  • real-time controls development
  • automotive powertrain systems and controls
  • vehicle dynamics
  • general dynamics
  • hydraulics
  • electric machines
  • batteries
  • internal combustion engines
  • mechatronic actuators
  • controls software for embedded targets using C or C++
  • Matlab/Simulink or Python for system modeling, simulation, scripting, and data analysis
  • Linux, Unix and Windows environments
  • unit testing platforms for tools development (pytest, Google Test, Ceedling)
  • standard systems engineering tools including boundary diagrams, fault tree analyses, FMEAs, P-diagrams
  • problem-solving
  • effective communication, documentation, and interpersonal skills

Nice to have

  • distributed systems engineering
  • requirements management
  • function decomposition and allocation
  • failure mode avoidance
  • robustness analysis
  • system validation and verification
  • modern build systems (Bazel, Gradle)
  • continuous integration and continuous delivery systems (Jenkins, GitHub Actions)
  • longitudinal controls for xEV systems
  • ISO26262 engineering tools
  • distributed system prototyping, troubleshooting, and commissioning
  • Matlab/Simulink for embedded controls development
  • standard version control and collaboration systems (ClearCase, AccuRev, git, GitHub)
  • CAE (MIL/SIL/HIL, virtual system/plant models, regression testing) concepts
  • CI (Jenkins, GitHub, Gradle) tools
  • automotive communication protocols (CAN, LIN)
  • analysis tools including CANalyzer, CANape, CANLab
  • Ford development processes GTDS and GPDS
  • Ford systems engineering systems and tools including VSEM, FEDE, Stages, FRD, HLF

What the JD emphasized

  • context-specific AI tools