To address some of the problems in existing distracted driving behavior detection methods, such as low detection accuracy and poor real-time performance, a deep learning-based target detection method was used for driver distracted driving behavior detection. Firstly, a distracted driving behavior dataset was constructed, including images of drivers using mobile phones, drinking water and smoking, and the targets were annotated, secondly a lightweight target detection model NanoDet was selected for training and validation. The results show that the method can accurately and quickly identify driver behaviors including using mobile phones, drinking water and smoking while driving.

A curve braking force control strategy was developed for vehicles equipped with Electro Mechanical Brake (EMB) systems. Firstly, the required braking force was obtained according to the driver’s expected deceleration, and then the braking force was initially distributed based on the vertical load estimate, and then the additional yaw moment control module designed based on the Active Disturbance Rejection Control (ADRC) algorithm was utilized to obtain the additional yaw moment required to improve handling stability of the vehicle, and finally the initially assigned braking force was adjusted through the braking force adjustment module. Simulink and CarSim were applied to co-simulate and compare with the proportional distribution scheme, and the results show that the four wheels are not easy to lock in curve braking when the control strategy proposed in this research is used, and the yaw rate and sideslip angle are closer to their ideal values, which effectively improves the safety of cornering braking.

To address the problems of small dataset and low efficiency of artificial diagnosis method in the research process of passenger vehicle abnormal noise recognition, this paper proposed an efficient intelligent recognition technique, which applied data expansion method with high recognition accuracy and adopted the parallel working mechanism of Convolutional Neural Network (CNN) and Transformer encoder stack to obtain the classification model. It is found that the data expansion method can effectively improve the classification performance when the extracted Mel Frequency Cepstral Coefficients (MFCCs) features of the augmented data are used as the input to the parallel network, and the proposed model can achieve classification accuracy up to 98.31% on the testing dataset.

For the influence of electromagnetic coupling vibration caused by random road excitation and unbalanced electromagnetic excitation of in-wheel motor on electric vehicle driven by in-wheel motor, this paper proposed a vibration suppression method based on Active Disturbance Rejection Control(ADRC). Firstly, the mathematical model of a quarter of the vehicle vibration system was established. Secondly, a controller based on ADRC was designed. The road random excitation and the electromagnetic excitation generated by the motor itself were regarded as the total disturbance for unified observation compensation control. Finally, the proposed control strategy was verified by MATLAB/Simulink. The results show that ADRC can suppress the electromagnetic coupling vibration caused by road roughness and eccentric electromagnetic force.

In order to study the noise source characteristics of integrated electric drive assembly, this paper proposed a joint algorithm of RVMD-RobustICA-ST combined with coherence analysis method. Firstly, the spatial dimension of the noise was estimated by Rule of Dominant Eigenvalues(RDE) based on Singular Value Decomposition(SVD), and the variational modal decomposition was subjected to targeted conditional constraints, and then Robust Independent Component Analysis(RobustICA) combined with variational modal decomposition to extract signal features. Secondly, S Transform and Fast Fourier Transform were used to identify the time-frequency characteristics of each component signal. Finally, on the basis of analyzing the waveform error of the component signal using the quadratic residual method, a linear system was established with the vibration signal, noise signal, and time-frequency overlapping component signal of the electric drive assembly as variables for coherence analysis. The results show that the meshing vibration noise of the second gear pair of the reducer has the greatest contribution to the noise of the electric drive assembly under steady state conditions, and the noise energy of the time-frequency overlapping component signal is mainly provided by the meshing vibration of the first gear pair of the reducer.

In order to meet the urgent demand of water-gas separation at the anode hydrogen outlet of the vehicle fuel cell stack and in view of the problems of large space occupation and low water-gas separation efficiency, this paper proposed a new box-type dual-baffle water gas separation device design based on the principle of baffle separation. Through CFD and finite element modeling and simulation methods, combined with the actual working conditions of hydrogen recirculation in a 60 kW fuel cell system, the separation efficiency of the device was simulated and analyzed. The influence of key factors such as inlet and outlet diameter, front and rear baffle length, distance from the inner wall, inclination angle, arc radius and angle on the separation efficiency was studied, and the optimal structural parameters of the device was determined which obviously improved the separation efficiency.

At present, the starting evaluation method of Dual Clutch Transmission (DCT) vehicles is mainly based on the driver’s subjective evaluation. Too much subjectivity leads to inaccurate evaluation. In view of the above problems, a DCT vehicle starting quality evaluation system was established based on the grey relational analysis method and the fuzzy comprehensive evaluation method. In this study, power, comfort and economy were considered, and starting quality evaluation indicators including starting response delay time, starting acceleration time, starting acceleration peak, engine speed fluctuation and shock were selected as evaluation index. The coefficient of variation method calculated the objective weight of the starting quality evaluation indicators, and based on the grey relational analysis method, the order of the correlation degree between each index and the starting quality was clarified, which verified the accuracy and reliability of the weight calculation results. Finally, based on the fuzzy comprehensive evaluation, the starting quality evaluation model of DCT vehicles was established and objectively scored, which made the starting quality evaluation of DCT vehicles more objective and true.

In order to verify the performance of vehicle under the functional interaction between Integrated Boosting System (IBS) and Electronic Stability Control (ESC), troubleshoot and locate the faults when IBS and ESC are interacted, this paper proposes a redundant brake electrical system multiple mechatronics Hardware In the Loop (m-HIL) testing platform scheme based on m-HIL technology, which could test function and performance of brake electrical system under functional interaction between IBS and ESC. According to the combined testing method, regenerative braking condition testing under IBS and ESC redundant controllers was accomplished. In addition, the parameter space corresponding to brake boosting failure under regenerative braking condition was abstracted, the typical test cases of braking boost failure under regenerative braking condition between IBS and ESC were formed.

In order to solve the shortcomings of current longitudinal collision avoidance technologies in specific scenarios such as high relative speed, poor road adhesion conditions and low overlap rate with obstacles, this paper studied the typical test scenarios and road tests of vehicle with less longitudinal distance and higher collision avoidance efficiency. Through analysis of the largest dada dataset for driving attention prediction in China, and in combination with the requirements of the EU ECE-R79 automatic steering standards, the typical test scenarios of Automatic Emergency Steering (AES) were obtained. At the same time, the road tests were designed, and a test software & hardware design scheme was proposed, which can monitor the emergency steering tests of different vehicle speeds under typical test scenarios, thereby realizing the effective test evaluation of the AES system.

For the characteristics of complex adjustment and control of the dot-matrix LED high beam lighting field, this paper analyzed the lighting requirements and luminous characteristics of the dot-matrix LED high beam, and then the mapping relationship between the dot-matrix LED high beam and the vehicle front lighting light field was established based on the geometric relationship, and a complete test system was built and tested. The test results show that the proposed method has accurate control effect, good real-time performance, high reliability and easy implementation.