In order to solve the problems of low efficiency and insufficient system scalability of single-machine test platforms in the vehicle-road-map collaborative simulation environment， a distributed autonomous driving simulation platform architecture for vehicle-road-map cooperative simulation is proposed in this paper， named VIMS （Vehicle-Infrastructure-Map System）. The VIMS platform uses CARLA as the virtual simulation engine. By introducing in real high-definition maps and connecting the hardware-in-the-loop devices such as driving simulators and signal machines to VIMS， the virtual-real traffic scene is formed. Considering the interaction of functions， the VIMS platform is divided into four modules， namely， the main world， the intelligent vehicle， the intelligent roadside， and the high-definition map， adopting ROS distributed architecture to realize the relative independence of the modules and interconnection between the modules. Considering the computational reliability and availability of the platform， distributed computing is used to realize independent computation among the four modules. Through the lane-keeping and vehicle-road-map collaborative positioning algorithm as examples for application validation， data acquisition， transmission and algorithm validation tests and evaluation are realized through the platform. The results show that the platform proposed in this paper can realize the real-time simulation of vehicle， road， and map collaboration to ensure that the modules operate organically and that the system architecture is highly scalable.

For the data imbalance problem of the current automotive CAN network intrusion detection algorithm due to the lack of attack samples， a CAN intrusion detection data enhancement method based on BEGAN is proposed， which introduces in one-hot coding to image the CAN message features and combines with the constructed Generative Adversarial Network to generate valid samples with the same format as the real attack and with different content. The practicality of the generated enhanced dataset is verified from the perspectives of feature maps， t-SNE visualization， statistical analysis and classifier validation by collecting real vehicle data as real samples for training， which can improve the intrusion detection classifier accuracy. With higher accuracy compared with the traditional oversampling algorithms including Random Oversampling （ROS）， Synthetic Minority Oversampling Technique （SMOTE）， SMOTE combined with Edited Nearest Neighbors （SMOTE-ENN） and Adaptive Synthetic Oversampling （ADASYN）.

The intelligent vehicle cyber-physical system （IVCPS） is a complex large-scale system with cross-fusion features across multiple fields. When designing domain-specific modeling languages （DSML） for IVCPS， the application of existing modeling languages has problems such as poor scalability， low maturity， and high learning cost. Therefore， based on the V-model and innovative architecture methods， this article studies the DSML for the IVCPS from two aspects： the top-level design process of IVCPS and the definition of language elements in the IVCPS meta-language knowledge set. The normalization of the IVCPS system-level meta-language and component-based meta-language is defined， and the components that express physical implementation， dynamic characteristics， and cyber computation in cyber-physical components are studied， so as to provide reference for the encapsulation and creation of cyber-physical components.

In order to reduce fuel consumption and transportation cost of heavy-duty truck， this paper coordinates the human-vehicle-road interaction system， integrates multi-dimensional information of vehicles and intelligent network environment， and proposes an adaptive range-domain predictive cruise control strategy （ARPCC） based on iterative dynamic programming （IDP）. Firstly， by combining the vehicle status and multi-dimensional information of the front environment， an adaptive distance domain model is established based on the longitudinal dynamics of the vehicle to reconstruct the road network， simplify the number of grids， and obtain the global optimal speed sequence by IDP. Secondly， on the basis of the global optimal speed sequence， the segmented optimal speed sequence taken from the adaptive distance domain is obtained to realize the fast solution of vehicle control state. Finally， Matlab/Simulink is used to verify the results， and the results show that the algorithm can effectively improve the computational efficiency and vehicle fuel economy by reducing the grid several times.

In this paper， an efficient forward collaborative design method for high-performance switched reluctance electric drive systems is proposed to enhance the power density and reduce vehicle loss under typical driving cycle conditions. Firstly， dynamic torque and radial force models of the switched reluctance motor are established. Subsequently， a loss model is developed for both the motor and the electric drive system by incorporating the gear transmission system's loss model to evaluate overall loss during typical driving cycle conditions. Finally， using mechanical， electrical， and control parameters as co-design variables and taking cycle loss， mass， torque fluctuation， and radial force fluctuation as optimization objectives， a double-layer nested optimization method is employed to optimize the design. Based on this approach， an optimized 12/8 grade switched reluctance electric drive system achieves a 19.76% reduction in total weight after collaborative optimization design. Moreover， under typical cycle conditions （CLTC-P）， the total system loss decreases by 42.45%， while overall system efficiency increases by 7.66%.

Accurate prediction of collision risk is crucial for ensuring the driving safety of intelligent vehicles. However， the risk differentiation among heterogeneity vehicle types and its coupled effect in longitudinal and lateral directions has rarely been considered in existing driving risk assessment methods. Therefore， firstly， the behavior patterns of drivers of heterogeneous vehicle types are explored to analyze the influence of vehicle types on drivers' sensitivity to risk in this paper. Secondly， the heterogeneous risk thresholds for different combinations of vehicle types are identified， and the risk differentiation in such traffic surroundings is further quantified based on two-dimensional indicators. Finally， the coupled two-dimensional collision risk prediction model considering vehicle types is proposed， and the effectiveness of the model is validated through comparative analysis. This research helps to enhance the driving safety of intelligent vehicles， which also can provide a theoretical foundation for the development of collision warning systems for human-driven vehicles.

Bipolar plates are one of the important components of hydrogen fuel cells. Titanium has many advantages as a metal bipolar plate substrate， but titanium has poor forming properties and severe rebound. In this paper， taking the micro channel hydroforming process of 0.1 mm TA2 pure titanium sheet as the research object， the microstructure deformation behavior of pure titanium is studied through the combination of experiment and finite element simulation， and the influence of process parameters on the forming quality of micro flow channel is analyzed， so as to provide guidance for the hydroforming of titanium bipolar plate. A finite element model has been developed for micro flow channel hydroforming of TA2 pure titanium sheet， and the accuracy of the finite element model is verified with the contours and thickness distribution of the test pieces. The effect of fluid pressure， loading rate and pulsatile loading on micro flow channel forming has been studied. The results show that the strain path of material in the process of micro flow channel hydroforming is plane strain， and the upper rounded corner position is the easiest to rupture. The loading rate does not have a great influence on the micro flow channel forming， and the molding depth decreases slightly by 3% with the increase of the loading rate. The pulsating loading path can improve the flow deformation ability of the material. Under the condition of critical fracture， the forming depth has a high increase compared with the linear loading path， which is up to 232.2 μm， an increase of 23%.

A study is conducted on the fatigue failure problem caused by the opening and closing of a car door. Firstly， the transient impact load under the door closing condition is discretized， and the vibration acceleration response signal and frequency response function are collected through the whole vehicle and bench tests respectively. Thus， the transfer path analysis （TPA） method is used to calculate the discretized transient impact load. Secondly， the obtained transient impact load is input into the finite element model of the door， and then the stress-time history response cloud diagram under the door closing condition is obtained， and the fatigue life under the door opening and closing condition is further calculated based on the fatigue damage theory. Finally， the fatigue analysis results based on load identification， the fatigue analysis results based on explicit dynamics and the fatigue test results under the door closed condition are compared and verified with each other. The conclusion shows that the three results are consistent， which has verified the rationality of the method.

As a three-phase power electronic device that emulates the characteristics of motor ports， the electric machine emulator （EME） provides an efficient test method for the testing of electric drive systems. The main sign of EME's restoration of the target motor port characteristics is to accurately restore the working current of the target motor， though the existing research has realized the reduction of the fundamental current and the lower order harmonic current， the restoration of the high-frequency ripple current of the motor driven by the motor controller still relies heavily on the matching of the filter inductor and the inductance of the target motor， which reduces the versatility of the EME. Therefore， based on the circuit equivalence virtual method， the equivalent circuit of PMSM is divided into two parts， with one part replaced by the actual circuit of EME， and the other part emulated by the control algorithm. Then， combining with the predictive control of the non-differential beat current， the control differential beat is compensated and the feedforward decoupling non-differential beat current following strategy is proposed. The experimental results show that based on the newly proposed port simulation algorithm of the permanent magnet synchronous motor， the EME can emulate PMSM with different parameters without replacing the inductor， with the frequency domain tracking error of high-frequency ripple current reduced from 160% to 20% of the traditional strategy， which significantly improves the emulation accuracy of the EME for the port-characteristics of PMSM.

For the problem that existing numerical simulation methods are unable to accurately reflect the probabilistic temperature variations caused by thermal runaway in lithium batteries， s a modeling method for the thermal runaway propagation of lithium battery modules based on probability function triggering is proposed. This method calculates the triggering probability of thermal runaway in each temperature range by statistical analysis of the temperature range and distribution of actual thermal runaway events in lithium batteries. Based on the proposed probabilistic trigger simulator， the simulation process is probabilistically triggered. The effectiveness of the method is verified by comparing simulation results with experimental data， showcasing a high degree of correlation. Then， the thermal spread paths and their probabilities under different triggering conditions of the probability function are analyzed， revealing multiple potential routes for thermal runaway， including the jump thermal runaway event. The sequential thermal runaway path is identified as the most probable， while the jump phenomenon is deemed least likely. The proposal of this method further improves the consistency between numerical simulation and actual process of thermal runaway in lithium batteries， providing an effective research tool and analysis method for studying the probability of thermal runaway propagation in lithium battery modules.