Research On Power Source Monitoring And Transmission System Of Hybrid Power Train

In order to solve the current problems of environmental protection and operation situations for urban rail transit, this paper aims to put the hybrid power system introduce to urban rail transit.A new type of hybrid electric train based on "net+ battery + super-capacitor" is one of the future directions of the train. The core of this paper is as follows:Firstly, this paper introduces the hybrid train energy transmission frame. Secondly, after building and analyzing for the core hub (parallel bi-directional DC/DC)model,it improves a new automatic current sharing technology. Finally, in order to verify the scheme is feasible, Simulation in Simulink is made. The results showed that parallel bi-directional DC/DC controller under the control of double closed loop can ensure the stability of output current and output voltage; In addition, with automatic current sharing technology, the average current of initial inductance dropped from 0.34 A to below 0.01 A, which proves the feasibility of this theoretical method.The core of the hybrid power source is lithium battery, so studying on lithium battery management is particularly important. At present, Equalization Control of charging Lithium batteries is the research hotspot. Against the particularity of the battery pack in train, in this paper, the simulation of balance control for the battery pack is made by MATLAB/Simulink. It verify the reliability and implementation by this control plan.When using the extended Kalman filter to estimate the electric vehicle lithium-ion power battery state of charge (SOC), the uncertainty of the system noise can cause algorithm convergence, and the algorithm of linearization much be affected by the model. In order to solve these two problems, this paper uses the improved Sage-Husa adaptive unscented Kalman Filters to dynamically estimate multiple lithium battery SOC. Simulation results show that compared with the EKF, the improve Sage-Husa adaptive kalman filters can improve the accuracy of the SOC estimation, and can real-time correct SOC estimation error caused by tiny model error online.The operation condition of the real time simulation are proved that the algorithm is more applicable to dynamic multiple lithium battery SOC estimate.At the same time, the state of health (SOH) is important parameters of power source. Firstly, in this paper, the monomer of battery pack is modeled. In addition, this paper adopts double DEKF estimation algorithm to the battery for SOH estimation. The last,the simulation proves the method has good effect.Finally, in accordance with the technical parameters and performance features of the hybrid power source, the paper has developed a test platform of hybrid energy storage component product. Based on the test platform, lithium battery charge and discharge characteristic test is made. It estimates the SOC and SOH of lithium battery online, real-time monitoring, recording and display system data, providing data report and dynamic curve, which supports the product of hybrid power train energy storage components.