Research On Multi-Rate Parameter Estimation And State Identification Methods Of Electric Traction Control System

Electric traction system is the power source for railway locomotives. The locomotive electric traction adopts high performance AC speed adjustment technology to meet the development of the railway system, thus the high performance field-oriented control (FOC) and direct torque control are the first choices of electric traction drive system. Speed sensor-less control of induction motor promotes the system robustness and reduces system cost. The key issues to be resolved of electric traction control system including:adhesion control, real-time state estimation of traction motor, real-time identification of important parameters.Different from the traditional digital system adopting a single sampling rate for all different signals, multi-rate system adopts different sampling strategies for different signals. Input multi-rate system increases the sampling speed of input, thus ability to control the system is improved, whereas the system could realize many control functions which single-rate system cannot. Output multi-rate system enables the controller to get more information of controlled object, thus system has a better control ability.Motor parameters may vary during motor operation. Among these parameters, rotor time constant is the most sensitive variable in FOC induction motor system. Its identification accuracy greatly affects the performance of traction control system. In view of the rotor time constant is time varying and difficult to measure, Using the principle that multi-rate control system has stronger control performance than traditional single-rate control system, combining multi-rate control method and model reference adaptive system (MRAS) method, the multi-rate MRAS parameter estimation method is proposed. Using the experiment set-up to validate the method, the comparison of parameter identification performance between multi-rate MRAS and traditional MRAS verified the proposed method is real-time and the proposed method has satisfactory dynamic and static estimation performance.Induction motor state estimation accuracy directly affect the performance of the system, at the same time the noise contained in state estimated value will affect the normal operation of motor system. Aiming at this problem, combining the extended Kalman filter (EKF) method and multi-rate control theory, the multi-rate EKF algorithm including input and output algorithms is proposed. A Hardware-in-the-loop (HIL) experiment set-up is proposed to validate the proposed method, comparing the state estimation performance between input multi-rate EKF method and traditional EKF methods under different frame period, the comparison verified the multi-rate EKF induction motor state estimation method is real-time, the method can effectively eliminate noise and improve the performance of state estimation and reduce the cost.Comparing with the EKF method, strong tracking filter (STF) has better robustness on model uncertainty and better tracking ability about abrupt state changes. In electric traction drive system, the load torque of traction motor changes quickly. Aiming at this problem, the multi-rate STF algorithm is proposed. By extending the single-axle locomotive model, a multi-axle model is proposed to simulate the real locomotive operation, the comparison between the model and actual slipping features verified the accuracy of the model. Using the proposed multi-axle model to validate the method, the method is applied to estimate the state of traction motor which is connected to the wheel-sets occur slipping phenomena, the result show that the multi-rate STF method has satisfactory estimation performance.The traction and braking of the electric locomotive is realized by adhesion force between wheel and rail. If the traction/braking force is greater than the available adhesion force between wheel and rail, the wheel-set will slipping/skidding, restricting the utilization of traction/braking force. It also will cause safety hidden trouble such as abrasion of wheel and rail, damage of wheel rim, even train derailment. Adhesion control method is adopted to improve the locomotive adhesion force. The slip/skid detection is the precondition of the adhesion control. To get accuracy rapid and effective slip detection, based on the principle that the response speed of electrical quantities is much faster than mechanical quantities in electric traction system, a slip detection method only based on electrical quantities is firstly proposed. The method is aiming to solve the disadvantage of present widely used adhesion control system in locomotive which is based on mechanical quantities such as wheel axle rotation speed. The electrical quantities based slip phenomena detection rules are designed based on the actual data obtained from the HXD2locomotive and the traction motor load torque multi-rate EKF state estimation method. Using the proposed model to validate the rules, the result show that the rules greatly reduced the slip detection time, avoid the severe loss of traction force, give full play to the locomotive traction power, and improve the overall performance and traction efficiency of the locomotive.