Abstract
Today’s automotive systems generally combine components from many different physical domains (electrics, mechanics, hydraulics, thermodynamics, electronics, control...). On the one hand, when attention is focused on details of one single domain, specific techniques and tools especially suited for the simulation of each field are available and widely applied, e.g., FEM, CFD, etc. On the other hand, when integrated analysis at system level is required, a completely different approach is generally considered: dynamic simulation tools (e.g. Matlab Simulink®) are used for modeling the vehicle systems or even the complete vehicle. Then, each domain is described using a reduced number of degrees of freedom, generally in the form of a lumped-parameter model. This way, the level of detail is given up in exchange of efficient calculations. However, there still exist cases in which the identification of model parameters becomes a very difficult task due to the presence of complex geometries or nonlinearities. In these cases, the cosimulation technique, consisting of the simultaneous execution of several simulation tools which exchange input/output information during the whole process, can be very beneficial. The cost for this extra potential is an increased computational effort that could make the system model inadequate for design optimization or software-in-the-loop simulations. To circumvent this problem, model order reduction techniques can be exploited to reduce the computational cost with a limited reduction of simulation accuracy. The work here presented concerns the development of a cosimulation framework for analyzing multidomain systems using Matlab Simulink© as core tool and third-party FEA-based simulators, as well as to the application of the proper orthogonal decomposition (POD) method to obtain reduced basis approximations for finite element models. A three-dimensional transient heat transfer finite element program has been linked to Matlab Simulink®, hence providing the capacity of simulating controlled electromechanical systems taking into account the strong coupling with the heat transfer processes in a complex geometry. Its application to control and system design in automotive industry is illustrated by the simulation of an Electric Park Brake system, in which the coupling between thermal, electrical and mechanical domains is essential for modeling and for the design of the control hardware. Using cosimulation and POD results in a straightforward method for including heat transfer through complex three-dimensional components in an accurate but computationally inexpensive way.
Keywords: Cosimulation, proper orthogonal decomposition, electric park brake, model order reduction