Sequential design of experiments for effective model-based validation of electronic control units

SummaryModel-based verification of automotive electronic control units (ECUs) must ensure compliance with the target requirements in a short time frame. On the other hand, an increasing number of sources of variability (e.g. operating conditions, block parameters) impact system performance. To reduce the overall verification effort, much focus has been put on performance in simulation, and little on how to plan simulation experiments to yield maximum information with minimum number of runs. This paper shows how the classical framework of statistical Design of Experiments can be extended to perform faster and more reliable multivariable sensitivity and worst-case studies. Simulation experiments of a state of the art ECU modelled in SystemC/SystemC-AMS show significant increase in efficiency as compared to traditional approaches.

[1]  Christoph Grimm,et al.  Modeling embedded systems using SystemC extensions , 2008 .

[2]  Iain Bate,et al.  Comparing design of experiments and evolutionary approaches to multi-objective optimisation of sensornet protocols , 2009, 2009 IEEE Congress on Evolutionary Computation.

[3]  Ying Chen,et al.  Microarchitecture-aware floorplanning using a statistical design of experiments approach , 2005, Proceedings. 42nd Design Automation Conference, 2005..

[4]  Frank Vahid,et al.  Soft-core Processor Customization using the Design of Experiments Paradigm , 2007, 2007 Design, Automation & Test in Europe Conference & Exhibition.

[5]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[6]  H. Theuerkauf,et al.  Robust identification of nonlinear dynamic systems using Design of Experiment , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[7]  Frank Ghenassia,et al.  Transaction Level Modeling with SystemC , 2005 .

[8]  Thorsten Grotker,et al.  System Design with SystemC , 2002 .

[9]  Jack P. C. Kleijnen,et al.  Design Of Experiments: Overview , 2008, 2008 Winter Simulation Conference.

[10]  Susan M. Sanchez,et al.  Work smarter, not harder: guidelines for designing simulation experiments , 2005, Proceedings of the Winter Simulation Conference, 2005..

[11]  Georg Pelz,et al.  Design of experiments for effective pre-silicon verification of automotive electronics , 2009, 2009 Forum on Specification & Design Languages (FDL).

[12]  Richard Stone,et al.  Automotive Engineering Fundamentals , 2004 .

[13]  Rob A. Rutenbar,et al.  Statistical Blockade: A Novel Method for Very Fast Monte Carlo Simulation of Rare Circuit Events, and its Application , 2007, 2007 Design, Automation & Test in Europe Conference & Exhibition.

[14]  Linda Trocine,et al.  An overview of newer, advanced screening methods for the initial phase in an experimental design , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[15]  Nicola Femia,et al.  True worst-case circuit tolerance analysis using genetic algorithms and affine arithmetic , 2000 .

[16]  Navakanta Bhat,et al.  Response surface modeling of 100 nm CMOS process technology using design of experiment , 2004, 17th International Conference on VLSI Design. Proceedings..

[17]  Russell R. Barton.  Designing simulation experiments , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..