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Sunday, September 11, 2011
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References :
Daiß, A. and Kiencke, U.: Estimation of Vehicle Speed - Fuzzy-Estimation in Comparison with Kalman-Filtering, 4th IEEE CCA, New York, 1995.
Ostertag, M.: Strukturierte Optimierung technischer Prozesse am Beispiel der KFZ Crasherkennung, Institute for Industrial Information Systems, University of Karlsruhe, Ph. D. dissertation, 1996.
Klein, R.: Realisierung einer Fuzzy-ABS-Regelung mit dem Mikrocontroller SAB 80C166 und dem Fuzzy-Coprozessor SAE 81C99A, Project work at the Institute for Industrial Information Systems, University of Karlsruhe, 1995.
Daiß, A.: Beobachtung fahrdynamischer Zustände und Verbesserung einer ABS- und Fahrdynamikregelung, Institute for Industrial Information Systems, University of Karlsruhe, Ph. D. dissertation, 1996.
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Antilock Braking System Using Fuzzy Logic
Antilock Braking System Using Fuzzy Logic
Abstract :
This paper deals with study and tests on an experimental car with antilock-braking system (ABS) and vehicle speed estimation using fuzzy logic. Vehicle dynamics and braking systems are complex and behave strongly non-linear which causes difficulties in developing a classical controller for ABS. Fuzzy logic, however facilitates such system designs and improves tuning abilities. The underlying control philosophy takes into consideration wheel acceleration as well as wheel slip in order to recognize blocking tendencies. The knowledge of the actual vehicle velocity is necessary to calculate wheel slips. This is done by means of a fuzzy estimator, which weighs the inputs of a longitudinal acceleration sensor and four wheel speed sensors. If lockup tendency is detected, magnetic valves are switched to reduce brake pressure. Performance evaluation is based both on computer simulations and an experimental car. To guarantee realtime ability (one control cycle takes seven milliseconds) and to relieve the electronic control unit (ECU), all fuzzy calculations are made by the fuzzy coprocessor SAE 81C99A. Measurements in the experimental car prove the functionality of this automotive fuzzy hardware system.
References :
Daiß, A. and Kiencke, U.: Estimation of Vehicle Speed - Fuzzy-Estimation in Comparison with Kalman-Filtering, 4th IEEE CCA, New York, 1995.
Ostertag, M.: Strukturierte Optimierung technischer Prozesse am Beispiel der KFZ Crasherkennung, Institute for Industrial Information Systems, University of Karlsruhe, Ph. D. dissertation, 1996.
Klein, R.: Realisierung einer Fuzzy-ABS-Regelung mit dem Mikrocontroller SAB 80C166 und dem Fuzzy-Coprozessor SAE 81C99A, Project work at the Institute for Industrial Information Systems, University of Karlsruhe, 1995.
Daiß, A.: Beobachtung fahrdynamischer Zustände und Verbesserung einer ABS- und Fahrdynamikregelung, Institute for Industrial Information Systems, University of Karlsruhe, Ph. D. dissertation, 1996.
View Full Paper: Click Here
Save Full Paper Via : Click Here
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