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.

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.

The waterthermal management system of a fuel cell is the core system that maintains the waterthermal balance of fuel cell engines. Factors such as flow rate, temperature and pressure distribution have significant impacts on the performance, power consumption, and reliability of fuel cell engines. Based on a 120 kWrated fuel cell engine, a theoretical basis for architecture design and component selection matching was provided from the perspective of optimal system function and performance. According to relevant design inputs and objectives, the modeling, simulation, and result analysis of the waterthermal management system were carried out using the onedimensional simulation software FloMaster. The distribution of flow rate, pressure, temperature, and velocity in the system under different operating conditions was evaluated, and verified through bench testing. The simulation and experimental results show that key technical indicators, such as the water pump flow rate, the temperature difference between the inlet and outlet of the fuel cell stack, and the inlet temperature of the fuel cell stack meet the system's target requirements under both rated and idle operating conditions.

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.

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.

This study focuses on a smallsized electric passenger vehicle equipped with a heat pump system, conducting a driving range test under lowtemperature CLTCP cycle conditions. By comprehensively examining the test data and analyzing the vehicle's energy flow, potential avenues for improving the driving range are explored. A comprehensive model of vehicle dynamics and economics, including the thermal management system, is established on the Amesim platform. After calibration, different optimization schemes are simulated and compared to develop a combined optimization scheme. Experimental results show that the combined optimization scheme can improve the lowtemperature driving range by 12.6%. Among them, the contribution of the thermal management system optimization scheme significantly surpasses that of the vehicle resistance optimization scheme and the control strategy optimization scheme. This study provides reference ideas and methods for improving the driving range of pure electric passenger vehicles under lowtemperature environments.

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.

This paper takes a light commercial truck as the subject of research, developing a carbon emission calculation model based on the life cycle theory. The model sets its boundaries at the stages of raw material acquisition, production and transportation, parts manufacturing and vehicle assembly in the automobile production process. The paper also explores the differences in the life cycle carbon emissions of the materials involved in the lightweighting measures, and compares the carbon emissions of the vehicle before and after lightweighting. The results show that the life cycle carbon emissions of the substitute materials such as aluminum, magnesium, and carbon fiber reinforced plastic are significantly higher than those of the substituted materials, steel and cast iron. The emissions are quantified as 6.23 kg/kg for forged aluminum, 6.92 kg/kg for cast aluminum, 14.76 kg/kg for magnesium products, 20.2 kg/kg for carbon fiber reinforced plastic, 2.85 kg/kg for ordinary steel, 0.67 kg/kg for stainless steel, and 0.81 kg/kg for cast iron. After lightweighting, the carbon emissions from the powertrain system, driveline system, chassis, and body parts increased by 0.57%, 525.51%, 11.57%, and 33.29%, respectively, leading to a total increase in the vehicle's lifecycle carbon emissions by 36.22%. Both steel and aluminum have lower lifecycle carbon emissions, which results in more significant carbon reduction effects in the vehicle body parts before and after lightweighting.

During the actual road driving test process, strictly controlling the driving state of heavyduty trucks can be challenging, which makes it difficult to directly evaluate the energy consumption levels from the test results. Therefore, this paper proposes an energy consumption evaluation method based on the division of driving characteristic intervals. Firstly, by analyzing the distribution characteristics of test points in the China Heavyduty Commercial Vehicle Test Cycle for Truck (CHTCHT), a division scheme for the number and boundaries of speed and acceleration intervals for heavy duty trucks is proposed. Then, considering the impact of road slope, the actual road test data is filtered and used to calculate the average fuel consumption across different driving characteristic intervals. Finally, based on the cumulative driving mileage within each interval of the CHTCHT, the energy consumption evaluation results are obtained. The validation is conducted using three chassis dynamometer drum tests and two actual road driving tests. The results show that the proposed method improves the reproducibility of actual road energy consumption evaluation results for heavyduty trucks.

Aiming at the current industry issue of inadequate testing and evaluation indexes for the driving experience of intelligent parking assist system users, the paper proposes both subjective and objective evaluation indexes for driving experience. These indexes are experimentally validated and analyzed for correlation. Firstly, based on the functional logic of the intelligent parking assist system, a driving experience closedloop control system is established. Subsequently, combined with the closedloop system, the subjective evaluation index system is constructed using the experience ladder pyramid model. Then, the objective indexes are developed by using the GSM model. Finally, realvehicle tests were conducted on seven car models and analysis was performed using Pearson correlation coefficients. The test results show that the proposed evaluation indexes are suitable for assessing the driving experience, with all subjective and objective correlation coefficients above 0.5, which provides guidance for the design and evaluation of intelligent parking assist systems.