TY - JOUR
T1 - A model-based design approach for simulation and virtual prototyping of automotive control systems using port-Hamiltonian systems
AU - Dai, Siyuan
AU - Zhang, Zhenkai
AU - Koutsoukos, Xenofon
N1 - Funding Information:
Acknowledgements The authors would like to acknowledge the partial support by the National Science Foundation under awards CNS-1035655 and CNS-1739328.
Publisher Copyright:
© 2017, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - Cyber–physical systems (CPS) such as automotive control systems consist of various interacting cyber and physical components. Heterogeneous domains, composition of multiple components, complex dynamics, and nonlinearities result in significant challenges for design, modeling, and simulation of CPS. Model-based design can be used to address such challenges, but it is very important to use physically accurate heterogeneous models that can be composed to represent the overall system behavior. Further, it is important to preserve the properties derived from analyses based on the mathematical models in the control system implementation in order to reduce costly testing and design changes late in the development cycle. This paper proposes a model-based design methodology for automotive control software using port-Hamiltonian systems (PHS). PHS are used to model the vehicle dynamics, speed and steering control systems, and the interactions between physical and cyber components. Passivity analysis is used to design the controllers and ensure system stability. More importantly, the proposed approach guarantees that passivity is preserved after time-discretization and quantization of the controllers. The models are then used for code generation and compilation, scheduling, and software deployment, ensuring that passivity is preserved by the control system implementation. We evaluate the methodology using an automotive control design case study implemented on a hardware-in-the-loop simulation platform and present simulation results to demonstrate its effectiveness.
AB - Cyber–physical systems (CPS) such as automotive control systems consist of various interacting cyber and physical components. Heterogeneous domains, composition of multiple components, complex dynamics, and nonlinearities result in significant challenges for design, modeling, and simulation of CPS. Model-based design can be used to address such challenges, but it is very important to use physically accurate heterogeneous models that can be composed to represent the overall system behavior. Further, it is important to preserve the properties derived from analyses based on the mathematical models in the control system implementation in order to reduce costly testing and design changes late in the development cycle. This paper proposes a model-based design methodology for automotive control software using port-Hamiltonian systems (PHS). PHS are used to model the vehicle dynamics, speed and steering control systems, and the interactions between physical and cyber components. Passivity analysis is used to design the controllers and ensure system stability. More importantly, the proposed approach guarantees that passivity is preserved after time-discretization and quantization of the controllers. The models are then used for code generation and compilation, scheduling, and software deployment, ensuring that passivity is preserved by the control system implementation. We evaluate the methodology using an automotive control design case study implemented on a hardware-in-the-loop simulation platform and present simulation results to demonstrate its effectiveness.
KW - Automotive control software
KW - Cyber–physical systems
KW - Model-based design
KW - Passivity
KW - Port-Hamiltonian systems
UR - http://www.scopus.com/inward/record.url?scp=85037646640&partnerID=8YFLogxK
U2 - 10.1007/s10270-017-0646-1
DO - 10.1007/s10270-017-0646-1
M3 - Article
AN - SCOPUS:85037646640
VL - 18
SP - 1637
EP - 1653
JO - Software and Systems Modeling
JF - Software and Systems Modeling
SN - 1619-1366
IS - 3
ER -