Laser transformation hardening is a key surface technique for improving the wear resistance and fatigue life of medium-carbon steel parts. However, predicting the resulting hardness distribution is challenging. Traditional experiments are destructive, and common simulations, which rely on equilibrium-based empirical models, lack accuracy for ultrafast non-equilibrium phase transformations. This study overcomes these limitations by developing a novel kinetic framework that captures the non-equilibrium phase transformation behavior during laser quenching, and establishes a high-fidelity hardness prediction methodology. The framework innovatively adapts the classical JMAK model to analyze the dynamic evolution of transformation mechanisms under ultrafast thermal cycles, building a parameterized model informed by physical data from isothermal transformation curves. This kinetics model is integrated with a microstructure-hardness mapping to form a comprehensive computational model. Experimental validation on various medium-carbon steels confirms the model's effectiveness in predicting hardened layer depth, microstructural distribution, and hardness gradients. This work thus provides a non-destructive, precise analytical tool for optimizing laser quenching processes and performance assessment of medium-carbon steel components.

Against the background of advancing commercial vehicle driving automation, the steer-by-wire (SBW) system has become a key research topic in the automotive field. To address the issues of high communication load, susceptibility of critical control messages to interference, and difficulty in rapid fault localization and handling in multi-controller network environments encountered in conventional SBW systems, this paper proposes an internal–external control decoupled redundant communication architecture for commercial vehicle SBW systems based on CANFD. The proposed architecture achieves physical decoupling between internal control communication and external vehicle communication. In addition, a fault detection and localization method based on heartbeat counter incremental propagation is developed, enabling rapid fault identification and master–slave switching control in multi-controller networks. An experimental platform is built using the NXP S32K344 microcontroller, and the communication strategy is developed and integrated within the AUTOSAR software architecture to validate communication real-time performance and fault tolerance capability. Experimental results show that the proposed architecture reduces the chassis CAN network load by approximately 26%, and the fault detection time is less than 50 ms. The findings demonstrate that the proposed architecture can effectively enhance the real-time communication capability and fault tolerance of commercial vehicle steer-by-wire systems.

Characterizing the constitutive relationship of stacked structures under combined stretching, torsional, and bending loading conditions presents significant challenges during the forming process of stator metal materials for permanent magnet motors, generators, and transformers. This study proposes a strain energy density-based multi-scale simplified equivalence methodology for complex working conditions. This approach reduces intricate processes or laminated configurations into simplified structural representations and loading scenarios to elucidate mechanical behavior under complex multiaxial loads. The equivalence framework encompasses forming process analysis, establishment of a strain energy capacity model, determination of specimen dimensions and experimental parameters via finite element analysis, and experimental validation through forming trials and material characterization techniques. Application of the methodology to analyze the forming process of stator coils within China’s high-speed train permanent magnet traction motors demonstrates mutual verification between strain energy density simulations and theoretical calculations. The comparative results between experiments and simulations for 4 size equivalent specimens are favorable under three test conditions: single bending, stretching bending, and torsion bending. This method effectively addresses the challenge of characterizing and experimentally validating prototype manufacturing processes for stacked structures under complex loading.

To synergistically optimize dynamic response, anti-disturbance capability, and parameter robustness in electromechanical servo systems. A composite control strategy is proposed. This strategy adopts an improved Dung Beetle Optimizer (HGVDBO) to automate the parameter tuning of a Linear Active Disturbance Rejection Controller (LADRC). The structure of the LADRC-based electromechanical servo system is designed at first. Then the improved Dung Beetle Optimizer (HGVDBO) is adopted by considering the difficulties of parameter tuning of LADRC and the requirements on accuracy and rapidity of the controller. The proposed HGVDBO - LADRC is compared with conventional incremental PID control through simulations and experiments. The results demonstrate that the proposed strategy achieves a 7.46 % reduction in step response adjustment time with nearly eliminated overshoot, and the maximum tracking error is close to zero under a 50 N pulse disturbance. Thus, the HGVDBO - LADRC can obtain a significant reduction in tracking error under various loading conditions, and it can also maintain stable performance during sudden load stiffness mutations. Its superior accuracy and robustness are verified.

The heat transfer process of medium carbon steel laser quenching has complex unsteady heat transfer characteristics, which are difficult to be accurately described by adopting traditional heat conduction models. The unsteady heat transfer control equation of medium carbon steel laser quenching considering the above influences is deduced, the heat conduction and temperature field variation laws of this process are explored, and a simulation model of unsteady heat transfer characteristics of medium carbon steel laser quenching is established. A laser quenching test system for medium carbon steel and measuring the temperature data during the actual quenching process is established to verify the reliability of the simulation method. The prosed heat source model for laser quenching on 45 steel surface has been proved to be effective by comparing the simulation results with the test ones.

The rail of high-speed railway is 500 m long and 30 tons in weight. Owing to the overweight and overlength characteristics of the rail, deformation occurs easily during transfer process. Thus, the clamping jaws should be synchronized in both longitudinal and lateral directions. The Space Vector Pulse Width Modulation vector control method is adopted to control the motors, which are used for driving the clamping jaws. The synchronization control of 32 longitudinal transfer motors is achieved using a mean coupling control strategy, while the synchronization control of 32 lateral transfer motors is achieved based on position feedback control by adopting the gray bus. Simulation results have shown that longitudinal synchronization error of the newly built transfer system is reduced by 74.06 %, compared with the previous system without synchronous control strategies. Field test results have verified applicability of the synchronous transfer control method, which has achieved less synchronization errors. The maximum error value is less than 60 mm between adjacent clamping jaws, and the entire system's synchronous error is less than 200 mm. The proposed transfer control method meets industry synchronization error standards and has demonstrated excellent practical performance.

This paper proposes a novel permanent magnet traction machine with a non-uniform air-gap rotor topology specifically designed for high-speed rail applications exceeding 400 km/h. The innovative rotor configuration could effectively suppress air-gap magnetic field distortion during high-speed operation, thereby reducing harmonic components in the magnetic field and minimizing core losses while enhancing overall efficiency. Firstly, the basic topology of the proposed non-uniform air-gap rotor is studied and the main design parameters of the traction machine used for high-speed rail train with speed over than 400km/h are analyzed. Secondly, the influence of main design parameters of the proposed rotor with non-uniform air gap on the key electromagnetic characteristics such as no-load characteristics, rated operating characteristics, losses, and efficiency is analyzed. Then, the no-load back electromotive force (EMF), rated torque, losses, efficiency and inductance of the proposed traction machine with non-uniform air gap are comprehensively analyzed based on the optimized structure. Finally, experimental validation through prototype testing confirms that the proposed non-uniform air-gap permanent magnet traction machine could successfully meet the operational requirements of high-speed rail train exceeding 400 km/h.

Determining the processing sequence of a set of workpieces involves continuous steps in real-world scenarios. The judgment is made based on partial observation of the environment, while the potential model of environment is still unknown. Reinforcement learning is a common approach to solve such problems, which can acquire knowledge through a series of rewards. A dynamic permutation flow shop scheduling algorithm based on transformer model is proposed to address the multi-disturbance problem in the permutation flow shop environment. The features of state matrix are extracted by adopting encoder based on transformer. The decoder is improved by adopting pointer network. The network model is trained by adopting Actor-Critic algorithm with baseline. In the Taillard data set, the average relative error of the proposed algorithm respectively is 2.48 %, 1.86 %, and 5.48 % lower than Campbell-Dudek-Simth (CDS), Palmer, and Convolution Back-Projection (CBP) algorithms, and average solution time is 0.61 seconds. It has been applied to the scheduling of rotor production disturbance in permanent magnet traction motor, and the efficiency has been improved by 2.59 %.

Electromagnetic wires, as various driving electrical components, are prone to stress concentration and fracture failure during the forming process due to their stacked structure. This article studies the mechanical properties of the loading sequence of tension bending and torsion bending combined working conditions in electromagnetic wire forming. Multiple load tests and simulations were used to describe the mechanical evolution of different loading sequences. X-ray diffraction and electron microscopy were used to analyze residual stress and characterize the microstructure of insulation damage. The influence of loading sequence on the mechanical behavior of electromagnetic wires and the damage of PI insulation layer was studied. The results indicate that the stress concentration area is smaller in the working condition of simultaneous twisting and bending, and the residual stress is lower compared to other working conditions. The condition of stretching first and then bending has lower residual stress compared to other conditions. Optimizing working conditions can reduce the risk of insulation damage.

This study innovatively integrates electromagnetic field finite element analysis, the Bertotti iron loss model, fluid dynamics modeling, and SKF bearing friction calculation models to establish, for the first time, a thermal network model for permanent magnet traction motors in unpowered transportation scenarios. This model enables precise analysis of the complex heating patterns within the motor and their heat transfer mechanisms. Through in-depth examination of this model, key factors influencing the motor’s temperature distribution are revealed. Based on these findings, during the design phase, methods such as optimizing the water-cooling structure and adding heat sinks to the end caps are proposed to effectively reduce the motor’s temperature in unpowered transportation scenarios, thereby ensuring safe transportation of the motor. Furthermore, for motors already installed on vehicles, this model can be utilized for precise analytical calculations to predict critical parameters such as safe towing speeds or continuous towing durations for safe operation. Therefore, this study provides practically guidance-oriented solutions for the optimal design and safe operation of permanent magnet traction motors, demonstrating its practical application value.

The semi-trailer ECPBS is adopted to achieve coordinated braking between tractor and trailer. Its control strategies are mainly verified through MIL and HIL tests. The correctness of the test results relies on the precision of the models. The dependence on the vehicle simulation models can be greatly reduced through an in-loop testing system, which combines the ECPB hardware test bench with the semi-trailer twin test vehicle. However, due to the long spatial distance between the two, higher requirements are placed on the real-time performance of the testing system. The communication interconnection mode, distributed network architecture, data coupling method and data coupling method of the in-loop testing system were investigated. Moreover, a delay compensation controller based on model prediction was designed and was applied to the motion control of the twin test vehicle. The simulation results have shown that the compensation controller can ensure the stability of vehicle motion with a goodness-of-fit of 0.826 under a delay of 0.7 s. Further experimental verification shows that the instructions issued by the ECPB hardware test bench controller can reach the semi-trailer twin test vehicle within 0.6 s, indicating that the communication interconnection method is feasible and can meet the real-time requirements of the in-loop testing system.

This paper presents an X-in-Loop test platform designed for the proof-of-concept testing of intelligent braking ECPBS in commercial vehicle. Firstly, the concept of intelligent braking is introduced, outlining its research scope and defining the necessary test requirements for the proof of concept. Based on these experimental criteria, the composition and operational principles of the proof-of-concept experimental platform are developed in accordance with X-in-Loop testing methodologies. The various subsystems and functionalities of the X-in-Loop proof-of-concept test platform are subsequently detailed. The working principle of the X-in-Loop proof-of-concept test platform is thoroughly explained using a loop example, and its workflow is presented. Finally, the platform’s fundamental functionalities are validated through a vehicle braking test conducted under specific working conditions, followed by an analysis of its potential applications.

Device-to-device (D2D) communication supports direct communications between nearby devices, which has potential to improve network capacity, spectrum efficiency and energy efficiency. Considering the high overhead to obtain the complete channel state information (CSI), we investigate resource allocation problems of D2D communication underlaying cellular networks with incomplete CSI to minimize the total power consumption. To deal with the challenge brought by incomplete CSI in estimating the instantaneous rates of D2D pairs (DPs), we consider two QoS metrics in terms of the expected rate and outage probability using statistical CSI. Based on that, we first investigate the energy-efficient power control problem for single cellular user (CU) and single DP sharing the same spectrum. With rigorous theoretical analysis of the intrinsic properties of CU rate and two QoS metrics, we design an optimal energy-efficient power control (EPO) algorithm for single CU and single DP. Using EPO as a building block, we then propose an energy-efficient resource allocation algorithm for multiple CUs and multiple DPs with incomplete CSI. Simulation results show that our algorithms consume the lowest powers compared with two baseline algorithms.

Facing the comprehensive promotion of CR450, permanent magnet traction motors need to be applied in batches. In response to the swift trial production requirements of various stator forming coil models in manufacturing and considering the correlation between design and manufacturing parameters, we research the geometric model of stator forming coils for manufacturing. In this study, the geometry modeling technique of the stator forming coil is elucidated. The essential structures are precisely modeled via the analytical geometry method. A correlation model illustrating the relationship between the design parameters and the manufacturing parameters of these structures is established to consider the calculation error. We propose a 3D scanning structural feature modeling approach that extracts coil features and employs fitting methods to invert key structural model elements on point cloud datasets for experimental validation. Leveraging the point cloud model, the critical structural size computation method is deployed to calculate structural parameters. The results demonstrate that the comparative errors in the span width and height of the nose end between forward and reverse modeling are 0.45% and 2.6%, respectively. This addresses the issue of design parameters being challenging to accurately guide manufacturing and can offer effective support for the design and manufacturing assembly of stator forming coils with various model specifications.

According to the principle of regional centralization and overall decentralization, K-means algorithm based on elbow rule was adopted to divide the equipment on the artificial colored-sand production line into several clustering partitions. The results were optimized to realize power balance between different partitions. Center of gravity method was adopted to determine the location of each control node. The goal of minimizing the total weighted distance from each equipment to its corresponding control node was achieved. Field results have shown that hardware and wiring cost of the production line has decreased by 13.32% and 20.41%, respectively.

The long body, high hazard factor and complex braking system of tractor semi-trailer make it difficult to conduct real-world tests in the development of the ECPBS (Electronically Controlled Pneumatic Brake System) controller. In order to reduce the number of real-world tests, accelerate the development of the controller and achieve rapid verification of the control strategy, this paper proposed a test system scheme integrating model-in-the-loop and hardware-in-the-loop test methods. Based on the circuit structure of the ECPBS of tractor semi-trailer, a model of the braking system was established using AMESim and embedded in the IPG simulation platform to realize the model-in-the-loop test function. An ECPBS controller was built based on the dSPACE real-time system and interconnected with a bench simulating the braking system of a real vehicle to realize the hardware-in-the-loop test function. A generic ECPBS control strategy was developed and tested on this test system. The results showed that the accuracy and reproducibility of the test system are well performed and can provide a reliable platform for the development of ECPBS controllers for tractor semi-trailer.

The automatic emergency braking (AEB) system of the passenger car is responsible for auxiliary braking judgment and decision-making in an emergency. Due to the inevitable pressure response delay of passenger car pneumatic braking systems, a large number of verification tests should be carried out to propose appropriate strategies and algorithms. To realize the rapid verification of the AEB control algorithm, a verification system integrating software-in-the-loop (SIL) and hardware-in-the-loop (HIL) was proposed for a two-axle passenger car. It can verify the logic feasibility of the control algorithm through SIL testing, and can verify the implementation effect of the control algorithm through HIL testing. The verification system is composed of IPG, dSPACE, and a pneumatic braking bench. Considering the influence of pneumatic braking delay, it is well-matched with the actual vehicle AEB system. The AEB hierarchical control algorithm was verified under three typical test conditions. The results show that the SIL testing results of speed and relative distance are in good agreement with the HIL testing results, and the average relative deviation of relative distance is only 1.7 m. The single test time of the SIL testing is about 228 s, which can meet the requirements of rapid verification of the AEB control algorithm of the passenger car.

Due to the slow assembly speed, large consumption of compressed air, and low qualification rate, the automatic assembly system for bolts and nuts in sets needs to be optimized urgently. The performance requirements of the system were analyzed, and the evaluation indexes of the system were proposed. Since the efficiency of the system mainly depends on the pneumatic components, the optimization work focuses on the pneumatic circuit. Parameters of the pneumatic circuit and pipeline were obtained through modeling and simulation. After parameter optimization, prototype test results have shown that the assembly speed and qualification rate of the optimized system is increased by 47.83% and 7.77%, respectively, while the air consumption is reduced by 23.39% compared with the original system.