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Advanced Engineering Intern: Model Predictive Control Development

Department: Advanced Engineering (80573)
Location: Plymouth, MI
Company Name: Isuzu Technical Center of America, Inc. (ITCA)

Brief Position Description:

The Advanced Controls Engineering team at ITCA is looking for highly motivated people to help us solve a complex engineering challenge in real time optimization and join us in developing it for production readiness. This internship is focused on control functions development for conventional light/medium duty truck (diesel) powertrain performance optimization. As an intern you would work with controls development team at ITCA and other stakeholders to realize model predictive control application for optimizing real time performance of Isuzu North America LD/MD truck powertrain. You will develop novel algorithmic solutions and software that meet ambitious specifications in terms of optimal control performance, computational performance, and reliability. Tasks would also involve utilizing Model Based Development (MBD) methodologies like MiL simulation, HiL testing, rapid software prototyping and real time testing. Application of theoretical knowledge of controls systems and knowledge of modelling and analysis of dynamical systems, to support ongoing project activities is expected.

Main responsibilities in this position are listed below:

  • Develop solutions based on Model Predictive Control using Matlab/Simulink primarily
  • Develop and improve dynamic plant models for integration into MPC solver
  • Formulation of the optimal control problem based on the requirements and constraints
  • Document code and evaluation results. Coordinate development efforts with other team members and manager

Other responsibilities would include and not limited to following:

  • Provides hands-on assistance to Engineers.
  • Supports testing, modeling and engineering operations as needed.
  • Acquires experience in different disciplines within the powertrain and vehicle development areas.

Internship Program Goals:

Continue ongoing efforts to support the realization of designed MPC architecture on real time target platform. Also includes optimization problem formulation, evaluation using Model-in-Loop simulation on desktop and Hardware-in-Loop test bench in closed loop with Real-Time (RT) plant model. Work with external organizations to gather technical support for implementation on real time embedded hardware.

 

 
 
 
 

 

 
 
 
 

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