Linking model predictive control (MPC) and system simulation tools to support automotive system architecture choices

Dirk von Wissel (1) , Vincent Talon (1) , Vincent Thomas (2) , Benoist Grangier (2) , Lukas Lansky (3) , Michael Uchanski (4)

1 Technocentre Renault [Guyancourt]
2 Siemens AG [Munich]
3 Honeywell International S.r.o. [Prague]
4 Honeywell

Today's automotive industry must introduce advanced powertrain technologies as a consequence of the stringent environmental regulations and strong market expectations. This leads to the increase of vehicle variants and to the growth of the powertrain architectures complexity. Hence, the development of hardware and software can no longer be decoupled. Those activities have to run in parallel, starting from simulation and advanced engineering, continuing to the detailed engineering phase, and ending in validation and calibration. In the so-called Model-Based Systems Engineering (MBSE) approach, simulation models including both hardware and control systems are used to first make decisions on possible architectures. This paper presents a new MBSE approach that allows powertrain hardware selection to occur early during the simulation stages. The process combines Model Predictive Control (MPC) for the control system with a physical modeling software package for the hardware. This combination of MPC and physical modeling addresses several practical difficulties that typically hinder attempts at MBSE for hardware selection.

Domaines: Systèmes embarqués

Dirk von Wissel, Vincent Talon, Vincent Thomas, Benoist Grangier, Lukas Lansky, et al.. Linking model predictive control (MPC) and system simulation tools to support automotive system architecture choices. 8th European Congress on Embedded Real Time Software and Systems (ERTS 2016), Jan 2016, TOULOUSE, France. ⟨hal-01289503⟩