Multi-level Idling Detection Of Heavy-duty Locomotive Based On Adhesion Coefficient Observer

With the increase of heavy cargo traffic,the traction power of the locomotive became higher and higher.The control objectives of the adhesive control system were not only to ensure steady operation of the locomotive but also to produce the maximum traction force allowed by the traction system.However,the operating environment of heavy-duty locomotive was complex and changeable while the adhesion between wheels and the rail was a complex process with large uncertainty.The adhesion system mainly consisted of idle testing module and protection action module,where the idle testing module transferred action commands to the protection action module.Therefore,real-time monitoring of the wheel-rail adhesion and actual determination on wheel/rail idling was the important conditions for realizing effective protection of the adhesion control system.The shortcomings of existing adhesion control method were discovered through the research in the paper and the method for the improvement was presented.The main research in the paper was as below:Through looking up of a large number of domestic and foreign literature,the adhesion theory is studied,and the adhesion between wheel and rail is analyzed.Then looking for the connection between adhesion and traction and a simple locomotive dynamic system was built.Existing adhesion control method was summarized,analyzed and compared.The adhesion coefficient and its derivative could not be measured directly.To solve the problem,a method for online estimate of adhesion coefficient and its derivative based on cascade sliding mode observer was presented.Through the wheel-rail dynamic analysis,the estimated values of adhesion coefficient and its derivative were obtained from those of load torque and its derivative based on he relationship between load torque and adhesion coefficient.Furthermore,the problem that the requirement on load torque was too stringent in existing method was also solved.The effectiveness of the algorithm was demonstrated by simulation and semi-physical experimental platform.A multi-level idling fault detection method was presented to facilitate idling fault detection.The shortcomings in existing method was discovered by the analysis on wheel/rail surface adhesion characteristics.The idling fault was classified based on different idling phenomena.The idling trend could be detected taking adhesion factor derivative as the criterion.Multi-level fault detection was conducted for idling of a locomotive adopting the method of adhesion factor derivative in combination with the acceleration.And the use of locomotive body speed signal was avoided and the reliability of the algorithm was improved significantly.