Research On The Real-time Algorithm For Multi-function Vehicle Bus Network

The multi-function vehicle bus MVB(Multi-function Vehicle Bus,MVB)is one of the standard of the IEC61375 international standard train communication network.Because it is specially designed for the application conditions and environment of the train communication network,it has high security,high reliability and high real-time performance.It has been widely applied to rail vehicle,high-speed train,EMU and other network communication systems.With the development of information technology and high-speed of train,the real-time performance of MVB communication has become the key factor to ensure the safety of train operation,as a field bus in the distributed network control system of the train,and has become a hot research topic in the train network control system.This paper mainly aims at the problems of poor configuration of periodic scanning table in periodic scheduling and long delay of data waiting in aperiodic scheduling on the multi-function vehicle bus.The knowledge-based cooperative particle swarm optimization and event arbitration algorithm based on reward and punishment mechanism are used to improve the real-time performance of MVB periodic data and aperiodic data scheduling.The specific research contents are as follows:First,based on the OPNET simulation environment,the MVB network,node and process model are built.Based on the built model,the performance of the network delay and bus utilization ratio of the multi-function vehicle bus communication network is tested and analyzed,and the test platform is provided for the follow-up algorithms.Second,in order to solve the problem of uneven distribution of periodic scanning table in the periodic data scheduling of multi-function vehicle bus,a knowledge-based collaborative particle swarm algorithm for scheduling optimization is proposed.The algorithm uses knowledge board to store data knowledge,uses multiple group data to guide and control node behavior,avoids excessive invalid search,optimizes global search,so as to optimize periodic scanning table.Based on the built MVB model,the performance of the periodic phase utilization ratio is simulated,and the MVB network bus utilization ratio before and after the optimization is compared.The results show that the algorithm effectively improves the real-time performance of the MVB periodic data communication.Third,in order to solve the problem of long time delay in event collision in aperiodicdata scheduling of multi-function vehicle bus,an adaptive event arbitration optimization algorithm based on reward and punishment mechanism is proposed.The algorithm adopts the reward and punishment mechanism to adjust the aperiodic data allocation,adaptively selects the equipment with less conflict,averages the bandwidth,manages the allocation problem of several small packets divided by aperiodic data,and designs a hardware event arbitrator based on the FPGA.Based on the built MVB model,the real-time performance of network efficiency and throughput is simulated,and the MVB network bus utilization ratio before and after optimization is compared.The results show that the algorithm effectively improves the real-time performance of MVB aperiodic data communication.By optimizing the MVB periodic scanning table and event arbitration mechanism,this paper improve the real-time performance of MVB network communication,provides a theoretical basis for customization of the MVB network control system,and provides a guarantee for the train safe operation.