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ECU DEVELOPMENT AND TESTING THROUGH NUMERICAL OPTIMIZATION AND HARDWARE IN THE LOOP SIMULATIONS
Technical Paper
2001-01-1865
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
A method to speed up and improve the whole development cycle of Electronic Control Units (ECU) is presented.
The proposed procedure can be divided into three steps:
- development and validation of the controlled system dynamic model;
- numerical optimisation of the system control strategy;
- Hardware In the Loop (HIL) simulations to test the electronic control unit.
Implementation of the method has led to the creation of a hardware in the loop system aimed at testing the control unit of electronically controlled transmissions. The system includes a Digital Signal Processing (DSP) board where the dynamic model runs and a console allowing the user to operate the throttle and brake pedals and to actuate the gearshifts. The behaviour of the model can be visualised through a real time Graphical User Interface (GUI) on a PC connected with the DSP board by a serial link.
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Citation
Paolo, B., Stefano, M., Giovanbattista, V., and Trifiletti, A., "ECU DEVELOPMENT AND TESTING THROUGH NUMERICAL OPTIMIZATION AND HARDWARE IN THE LOOP SIMULATIONS," SAE Technical Paper 2001-01-1865, 2001, https://doi.org/10.4271/2001-01-1865.Also In
References
- Cossalter, V. 1999
- Kienke, U Nielsen, L Automotive Control Systems Springer 2000
- Jurgen, K. R. Electronic Transmission Controls SAE PT-79 Society of Automotive Engineers, Inc. Warrendale, PA 2000
- Automotive Handbook Bosch 4th
- Milliken, W.F. Milliken, D.L. Race Car Vehicle Dynamics SAE R-146 Society of Automotive Engineers, Inc. Warrendale, PA 1995
- Goffe, Ferrier Rogers Global Optimization of Statistical Functions with Simulated Annealing Journal of Econometrics 60 1 2 Jan. Feb. 1994 65 100
- Goldberg D.E. Genetic Algorithms in Search Optimisation and Machine Learning Addison-Wesley 1989