With a light truck equipped with power-following fuel cell as the research object, a power-following energy management strategy of a fuel cell based on wavelet transformation has been constructed combining the frequency characteristics of the vehicle power demand under typical driving cycles using wavelet analysis method. The low frequency component of the vehicle power demand obtained after wavelet transform was allocated to the fuel cell, so as to improve the fluctuation of the fuel cell output power. In addition, the wavelet decomposition level was dynamically adjusted to regulate the power following degree automatically, to ensure the power supply of the vehicle under various power battery charge-discharge capacity and vehicle power requirement. The simulation result shows that the power-following allocation strategy based on wavelet transform can meet the vehicle power demand under typical driving conditions, and the SOC can be kept in the reasonable range, the power output fluctuation of the fuel cell has been decreased by 29.8%, in addition, the hydrogen consumption has been reduced by 1.5%.

In order to solve the problem of low accuracy in predicting the remaining service life of proton exchange membrane fuel cells, this paper proposed a dynamic fuel cell Remaining Useful Life (RUL) prediction model based on Northern Goshawk Optimization (NGO), Convolutional Neural Network (CNN) and Bi-directional Long Short-Term Memory (BiLSTM) neutral network. Firstly, NGO optimized the learning rate, hidden nodes and regularization coefficient of the CNN-BiLSTM model, and then the CNN-BiLSTM model extracted the features of the input data through the convolutional layer, and input it into the BiLSTM layer for timing modeling and prediction. In addition, wavelet threshold de-noising algorithm was used to smoothen the original data. Pearson correlation coefficient was used to extract model input variables, and NGO-CNN-BiLSTM network power prediction model was built. The simulation and verification results show that this method can effectively improve the prediction accuracy of the remaining service life of fuel cells up to 99.49%, which is higher than that of other comparative models.

In the state-of-charge estimation of power battery, the traditional Extended Kalman Filter (EKF) ignores high-order terms and Particle Filter (PF) suffers from particle degradation and loss of diversity during the resampling process. To address this issue, this paper proposed the improved Mixed Kalman Particle Filter (MKPF) algorithm. Firstly, the extended Kalman filter was used to generate the state estimate of the system, and then the unscented Kalman filter was used to repeat the process. The state estimates obtained by the extended Kalman filter and the unscented Kalman filter were used together as the particle filter proposal distribution, and value sorting was used to determine the survival of the fittest particles. Simulation and experimental results show that the maximum error of SOC estimate by the proposed algorithm is 1.2%, which is better than the estimation accuracy of the existing PF, EKF, and UKF algorithms on SOC.

This article analyzed the technical requirements of hydrogen sensors used in fuel cell vehicles, and studied the working principles, characteristics of various vehicular hydrogen sensors, compared the performance and parameters of mainstream hydrogen concentration sensors at present, summarized and analyzed the current development status of hydrogen concentration sensors. The technical development trend of hydrogen concentration sensors was predicted based on industry development needs.

In response to the lack of research on the performance, standards, and testing methods of Intelligent Speed Assistance (ISA) system for motor vehicles in China at present, this paper introduced the working principle of ISA, studied the typical test scenarios specified in EU 2021/1958. On this basis, a motor vehicles’ ISA performance testing system and scenario were developed and a road test of a passenger car’s ISA performance was carried out according to the standard. The results indicate that the test vehicle’s ISA system complies with the requirements of EU 2021/1958 and the higher the vehicle speed, the later the ISA system will recognize the speed limit sign and when developing ISA systems attention should be paid to the sensitivity of the ISA system to recognize the speed limit sign when the speed is high.

To achieve the coupling analysis of the flow field, temperature field, and structural field of the intercooler, Computational Fluid Dynamics (CFD) and thermal strain test methods were used to conduct coupling analysis and experiments on the flow field, temperature field, and stress field of the intercooler using a fluid thermal structure coupling method. The flow field structure, temperature, and stress distribution of the intercooler were obtained. The analysis results show that this method can effectively predict the flow field and temperature field of the intercooler.

This paper analyzed the cause of a 1.5 L naturally aspirated engine’s intake manifold mounting support cracking in bench test and design was optimized. The electron microscope analysis results show that fatigue cracks exist on the fracture surface of the failed support, and the main cause of the support cracking is found to be the resonance caused by the large vibration at the far end of the intake manifold through engine bench vibration test and test boundary checking. The material of the support was adjusted from SUH409L to QT500, simulation calculations and experimental verification were conducted on the new support, and no cracking was found on the new support.

The odor of four types of leather fabrics for vehicles was evaluated, and the odor substances were tested by Thermal Desorption Gas Chromatography Odor detector/Mass Spectrometry (TD-GC/OMS), and the sources of main odorants were further analyzed. The research shows that the odor substances of leather fabrics mainly come from the solvents, additives and related reaction products used in the processing, and part of them come from the volatilization of leather fabrics itself.

For the selection of vehicle trumpet based on vehicle test, there are problems of operation lag and affecting the progress of mass production of models. To address this issue, this paper proposed a trumpet near-field sound pressure simulation method based on Ray Tracing. Firstly, the hard wall panel data on the external surface of a vehicle was extracted, and Ray Tracing model solution model was established in VAOne, then the sound power of the trumpet was obtained by the inverse matrix module that was loaded into the Ray Tracing solution model to calculate the near-field sound pressure. The near-field sound pressure of trumpet simulation was compared with the test results, the result shows that the calculated near-field sound pressure value of trumpet is in good agreement with the experimental value, which can provide basis for vehicle trumpet selection in the early stage of model development.

In order to ensure that the automotive generator can meet the power supply requirements under different operating conditions of the vehicle, the influence of the parameters of the automotive AC generator stator assembly on the rated power and output characteristics of the generator was analyzed and verified. The results show that, under the condition of stator core size specifications unchanged, the rated power can be increased without changing the slot filling rate and reducing the number of turns, but the output power can be reduced under low-speed conditions. Changing from star connection to triangle connection or adding a neutral point can increase the rated power without changing the low-speed output power. Changing the three-phase armature winding to six phases hardly affects the rated power and output characteristics, but can reduce the ripple peak value of the output current.