Supported by the dualcarbon goal and various new energy policies, the hydrogen energy industry has experienced rapid development. As the hub of upstream hydrogen production, midstream hydrogen storage and downstream application markets in the hydrogen energy industry, the construction and development of hydrogen refueling stations are inseparable from safety risk assessment. In this study, a quantitative risk assessment method for hydrogen refueling stations was established, and a quantitative risk assessment software Safeti was used to evaluate the risk of a hydrogen refueling station. Based on the individual risk contours and social risk analysis results, the accident risk level of the hydrogen refueling station was determined. Finally, to ensure the safety of hydrogen refueling stations, risk prevention and control measures are proposed from the aspects of standards, safety systems and institutional frameworks.

To effectively reduce the noise of the fuel cell centrifugal air compressor system, a perforated muffler capable of broadband noise reduction was designed. Using the method of computational fluid dynamics coupled with computational aerodynamic acoustics, the noise reduction effect of the perforated muffler was analyzed under different operating conditions of the compressor. Additionally, the thermoacoustic transformation relationship inside the muffler was quantified. The results show that the cavity thickness and perforation rate of the perforated muffler play a decisive role in absorbing highfrequency sound wave components. Compared with the lowfrequency sound waves, the perforated muffler is more effective at attenuating highfrequency sound wave components. As the rotational speed increases, the muffling effect on the highfrequency components gradually enhances, while the effect on the lowfrequency components remains almost unchanged. The thermalacoustic conversion analysis of the perforated muffler shows that under lowspeed operation conditions, the energy of acoustic oscillation before and after muffling is almost completely converted into the exergy of the air. In contrast, under medium and highspeed operating conditions, the proportion of acoustic oscillation energy converted into air exergy is relatively small. To design a muffler that can achieve broadband noise reduction under various operating conditions, the attenuation of lowfrequency sound waves at high rotational speeds should be the primary optimization target. The improvement of thermodynamic performance before and after muffling at low rotational speeds should also be considered. The work presented in this paper provides a new method for reducing the aerodynamic noise of centrifugal air compressors, and offers a theoretical basis for designing highefficiency air compressor mufflers with wide working condition adaptability.

Focusing on the hydrogen ejector used in fuel cells, a CFD simulation model was established to study the influence of structural parameters, such as the nozzle throat diameter D, the nozzle angle ø and the mixing chamber diameter D, on the ejector's performance. The results show that the influence of structural parameters on the ejector's performance varies across different power levels of the fuel cell stack. In the lowpower range, the entrainment ratio significantly increases with the nozzle angle, while in the highpower range, the entrainment ratio decreases as the nozzle angle increases. The influence of the mixing chamber diameter on the ejector's performance is opposite. In the lowpower range, the entrainment ratio decreases as the mixing chamber diameter increases, while in the highpower range, the entrainment ratio increases with the mixing chamber diameter. Based on the influence patterns, the design method for key structural parameters of the ejector was developed, and the optimal parameter range was obtained.

Taking a fuel cell electric light truck as the research object, a simulation model of the power system was built using Matlab/Simulink, in order to improve the economic efficiency and durability of the fuel cell system through the optimization of its energy management strategy. Based on the foundational fuzzy control, an improved fuzzy control strategy was developed to restrict the rate of change in the fuel cell output power. The performance of this strategy was compared with the finite state machine control strategy and the original fuzzy control to validate the simulation. The simulation results show that, under the NEDC and UDDS cycle conditions, the hydrogen consumption of the improved fuzzy control strategy is reduced by 5.65% and 8.29% respectively compared to the original strategy. Compared with the finite state machine control strategy, the improved fuzzy control strategy yields a reduction in hydrogen consumption by 16.63% and 10.64% with smaller fluctuations in the fuel cell output power, which results in a more stable performance and enhanced economic efficiency and durability of the fuel cell system.

Focusing on the thermal management and waste heat recovery of a fuel cell bus, an integrated vehicle thermal manage system is developed, and 9 corresponding operation modes are proposed. A simulation mode is established based on AMESim to analyze the temperature control characteristics and energy consumption of the system under high, low and extremely low temperature conditions. The results show that under hightemperature conditions of 34, 37, 40 °C, the thermal manage system can maintain key components within an appropriate temperature range to meet their respective cooling requirements. Under lowtemperature conditions of 10, 5,0,5 °C, the thermal management system can meet the heating needs of the key components. Additionally, the waste heat from the fuel cell stack and motor can meet the cabin heating requirements when the ambient temperature is above 15 °C. This can save up to 10.44% of the vehicle's driving energy consumption compared to using pure PTC for cabin heating. Under extreme cold conditions of 30, 25, 20 °C, the waste heat alone is insufficient to meet the cabin heating demand, requiring the use of PTC for auxiliary heating. The additional equivalent hydrogen consumption for PTC heating is 44.10, 36.89, 33.5 g, respectively.

Automated Valet Parking (AVP) system is a comprehensive platform integrating intelligent driving environment perception, decision planning and motion control technologies. Trajectory planning is directly related to the efficiency, energy consumption, safety and comfort of the valet parking process. To outline the development status of autonomous parking trajectory planning technology, this paper first reviews the development history of parking technology, then investigates trajectory planning during parking, and analyzes the progress in AVP research. Recognizing that the transition from singlevehicle intelligence to multivehicle cooperation reveals greater potential for system optimization, this study subsequently outlines the fundamental methods and current research status of multivehicle cooperative trajectory planning, with a special focus on cooperative planning in parking scenarios. Finally, this paper analyzes existing issues and future development trends in AVP trajectory planning.

As one of the most commonly used modes of transportation, the majority of automobiles are in the L2 to L3 stage of humanmachine codriving technology development. Before the emergence of L5level autonomous driving technology, “humanmachine codriving” remains the dominant driving method, with its various invehicle systems and interaction methods continuously being improved. The integration of multimodal interaction with automotive technologies is bound to ignite new "sparks" as a future design trend. This paper firstly summarizes the research on multimodal interaction design for invehicle systems, covering directions such as fatigue warning, collision warning, lane departure warning, intelligent takeover reminder, and intelligent parking. Subsequently, it analyzes the natural interaction methods of invehicle AI multimodal interaction design, including multiscreen interaction, touch interaction, gesture interaction, voice interaction, facial expression interaction and eye movement interaction. The article uses literature research and case studies to explore how to improve the driver's comfort in the context of safety and emotional aspects, and anticipates the applications and future trends of multimodal interaction design for invehicle systems. Finally, it is concluded that the integration of appropriate and effective interaction methods will improve the safety and driving comfort of various invehicle systems and applications. The introduction of multimodal interaction is destined to become a trend in automotive development.

In order to promote the development of autonomous vehicle applications, conducting accurate and reliable safety testing and evaluation is essential. This paper proposes a safety evaluation method for autonomous vehicles tailored to highspeed ramp traffic scenarios using natural driving data. By analyzing the conflict characteristics in the confluence area, the models for calculating traffic conflict indicators such as TTC, PET and MSS are established to determine the safety evaluation indicators. The fuzzy clustering of natural driving indicator data is used to obtain the threshold ranges for these indicators. The autonomous vehicle simulation test has been built. The importance criterion weight distribution method based on interlayer correlation and the gray correlation scoring model are applied. The comprehensive evaluation scores regarding the safety of autonomous vehicles are calculated under different control algorithms. The results show a distinct correlation in the distribution of safety indices between the test vehicle's driving behavior and ideal driving behavior. By calculating the overall correlation degree, the scores can directly reflect the comprehensive safety performance of different autonomous driving systems.

To meet the requirements for testing and evaluating ADAS systems in lane change cutin scenarios, the paper proposes a method for generating such scenarios and an objective, comprehensive evaluation model considering the scenario risk coefficients. By collecting natural driving data, the threshold method is used to automatically extract lane change cutin function scenarios and deeply analyze the lane change cutin behavior characteristics. The correlation between scenario risk coefficients and scenario elements is jointly analyzed using oneway ANOVA and Pearson's correlation test to identify key scenario elements. Furthermore, by applying the Kmeans clustering method to the parameters of discrete logic scenarios, five typical test scenarios are obtained. Based on the scenario risk coefficient, the AHP and CRITIC methods are used to construct a multilevel comprehensive evaluation model. The ADAS system is objectively evaluated using the gray correlation theory. Finally, the VTD simulation software is used to create a virtual test scene library for lane change cutin scenarios for simulation testing and validation. The results show that correlation analysis reduces the dimensionality of scenario elements by 60%. The generated test scenarios can effectively validate the comprehensive performance of the ADAS system. Moreover, the comprehensive evaluation model can objectively and effectively evaluate the performance of the ADAS system, providing a valuable reference for the development of intelligent driving systems.

The HMI intelligent system in the vehicle cabin significantly influences the user's intelligent experience. Testing and researching HMI leads to the establishment of a complete set of HMI testing and evaluation methods, which can guide the design and development of HMI, achieving iterative improvement and optimization of HMI systems. The increasing number of features in the car cabin provides users with a richer experience. However, even with identical functionalities, different HMIs can result in vastly different driving experiences for users. This article, based on typical usage scenarios, objectively analyzes the differences in the system response, driver's eye movements, and hand activities across different vehicle models under the same scenarios. The evaluation parameters are further quantified to form assessment indicators. Additionally, a subjective evaluation form is designed based on the five senses and perceptions to evaluate the HMI. The evaluation results indicate that this method is practical and reasonable, and can comprehensively evaluate the advantages and disadvantages of the HMI from both objective and subjective perspectives.