This paper presents a complex product design-manufacturing-operations and maintenance integration method based on digital twin technology. This method aims to solve the problem of information silos in the design, manufacturing and operation and maintenance phases of complex products in the context of intelligent manufacturing and to integrate the design, manufacturing and operation and maintenance processes of complex products. To address the integration needs of complex product design, manufacturing, operation and maintenance business integration, a framework for complex product design-manufacturing-operation and maintenance integration based on the digital twin is first proposed, in addition to designing a model and operation mechanism for combining the virtual and real of the digital twin model. Then, the implementation of multistage collaborative design technology, data intelligent sensing technology, and data integration and fusion technology for the digital twin-based design-manufacturing-operations and maintenance integration processes are analyzed and discussed. Finally, a case study involving the fault prediction of key components of the bogie of an EMU demonstrated the integrated mode of operation in the design-manufacture-operation and maintenance process of the EMU. It verified the effectiveness of the proposed framework, process and methodology.

This article introduced a positioning system composed of different sensors, such as LiDAR, IMU, and ultra-wideband (UWB), for the positioning method in autonomous driving technology under closed coal mine tunnels. First, we processed the LiDAR data, extracted its feature points and merged the extracted feature point clouds to generate a skewed combined feature point cloud. Then, we used the skew combined feature point clouds for feature matching, performed pre-integration processing on the IMU sensor data, and completed the LiDAR-IMU odometer with the LiDAR. Finally, we added UWB data to IMU pose node as a one-dimensional over-edge constraint. By updating the sliding window, the positioning accuracy was further improved. Moreover, we have conducted experiments to verify the proposed positioning system in a simulated roadway. The experimental results showed that the method proposed in this paper is superior to the single LiDAR method and the single UWB method in terms of positioning accuracy.

The development of the automobile industry and the increase in car ownership has brought great traffic pressures to the city, among which, the difficulty of parking has become a serious problem to the majority of drivers. An automatic parking system can help drivers to complete parking operation or automatic parking task, and a decision control system is an important part of automatic parking system. In this paper, a strategy for generating the shortest parking path based on a bidirectional breadth-first search algorithm combined with a modified Bellman–Ford algorithm is proposed for automatic parking systems. Experimental results show that this scheme can improve the performance of an automatic parking system, especially in a complex environment.

Four-wheel independent drive electric vehicles have become the latest development trend of electric vehicles due to their simple structure and high control accuracy. Aiming at the sliding problem of four-wheel independent driving electric vehicles in the driving process, a driving anti-skid control strategy is designed. The strategy includes two contents: (1) a road recognition module that tracks the best slip rate in real time; (2) a slip rate control module that uses fuzzy PID control. Then, based on Carsim and MATLAB/Simulink, the vehicle dynamics model, tire model and driving anti-skid control model are established. A simulation of the driving anti-skid control algorithm is carried out to verify the feasibility of the control strategy. Finally, based on the built-up dSPACE semi-physical experimental simulation platform, the verification was carried out, and the test and simulation results were compared to verify the effective feasibility of the driving anti-skid control strategy.

Lithium-ion batteries which are used in electric vehicles cannot be charged to their maximum capacity at the end of the charging period, a situation which is caused by inconsistency between the battery cells. This paper takes the 18650 ternary lithium battery as the research object and proposes an alternate equalization control system in the charging process. This system takes SOC consistency to be the equalization variable. Through controlling the relay, this system realizes the alternate recombination between different batteries in order to form a series battery group for charging, which achieves the goal of SOC equalization of the entire battery group. The simulation result of charge equalization, based on Matlab/Simulink, shows that at the end of the charging simulation, the SOC inconsistency of the battery group reduced from 10% to 1%. Finally, an experimental platform was built in order to verify the experiment. During the charge balance experiment, the maximum SOC inconsistency between the batteries reduced from 1.542% to 1.035%. The SOC inconsistency at the end of charging reduced from 1.214% to 0.8%, which represents an improvement of the equalization effect of the control system. The experimental results are consistent with the simulation results, which proves the effectiveness of the system’s ability to control the battery SOC balance during the charging process.

In order to improve the stability of vehicle steering on low-adhesion road surfaces, this paper designed a hybrid robust control strategy, H₂/H_∞, for active front-wheel steering (AFS) based on robust control theory. Firstly, we analyzed the influence of the sidewall stiffness and road adhesion coefficient of the tires on vehicle stability, through which we can study the wheel deflection characteristics of low-adhesion roads. Secondly, the reference yaw velocity of the vehicle was calculated using the three-degrees-of-freedom model as the reference model, through which, taking the norm H_∞ as the objective function and the norm H₂ as the limit to control the output, the hybrid robust control strategy H₂/H_∞ of the AFS system on a low-adhesion road surface was developed. Finally, the simulation experiment was carried out by the Simulink/CarSim co-simulation platform and a hardware-in-the-loop (HIL) experiment. In this paper, the results show that the AFS control strategy can improve the vehicle handling stability on low-adhesion road surfaces, and the controller has good path tracking performance and robustness.