Collaborative lane change technology for intelligent connected vehicles has been widely studied，but existing strategies can hardly solve the problem of vehicle collaboration in mandatory lane change scenarios or may cause notable impact on upstream traffic. For mandatory lane change scenarios demand，a two-stage cooperative lane change strategy considering theoretical minimal safety space is proposed in this paper. Firstly，the control architecture for a two-vehicle cooperative lane change system is proposed and a collaborative lane change scheme is developed for mandatory lane change scenarios. Then，a two-stage receding-horizon trajectory planning strategy of spacing adjustment and collaborative lane change is designed，where the theoretical minimum safe distance is embedded as a constraint of spacing adjustment stage，to solve the problem of conservative spacing strategies in existing research. Finally，numerical simulation and hardware in-loop experiments are performed to verify the effectiveness，advantages and computational real-time performance of the proposed strategy. The results show that the proposed strategy can effectively improve the success rate of lane change，reduce the negative traffic impact while ensuring lane change safety，and is also applicable in real time computing and communication environment of actual edge cloud platform.

In order to optimize the cold start process of PEMFC，it is essential to provide sufficient feedback data. Common impedance spectroscopy and equivalent circuits cannot provide sufficient and real-time feedback due to long acquisition period. Therefore，the cold start impedance model is developed in COMSOL，and the change of impedance spectroscopy is analyzed in combination with experiments. The characteristic frequencies of 1kHz，50Hz and 1Hz are proposed in the high，medium and low frequency ranges respectively to characterize the cold start process of the fuel cell. The results show the above characteristic frequencies vary significantly in the pre-，mid- and post-cold start phases，with the change in impedance at characteristic frequencies of 1 kHz，50Hz and 1Hz of 0.38，0.31 and 1.47 respectively. It improves the real-time performance of data acquisition while retaining feature information compared to obtaining the full impedance spectroscopy and fitting the equivalent circuit. Therefore，the impedance at the characteristic frequency points can be used to characterize the cold start process，which provides real-time monitoring for the internal state of the cold start.

In order to improve the traffic efficiency and fuel utilization efficiency of intelligent connected vehicles （ICVs） under urban traffic networks，a multilane spatiotemporal trajectory optimization method is proposed in this paper. Firstly，the state and constraints of the ICVs are defined based on the multi-lane spatiotemporal position relationship and the compound optimization model of spatiotemporal trajectory is constructed by considering the traffic efficiency and fuel economy，which is solved by the Pontryagin Maximum algorithm. Furthermore，the rules of cooperative lane change are designed to obtain the optimal lane change strategy by Q-learning algorithm. Finally，the SUMO/Python co-simulation tests show that the method can effectively improve the traffic efficiency under different vehicle saturation levels，split allocation，and minimum traffic speed conditions，with great improvement of fuel efficiency.

Carbon reduction in commercial vehicles has become a key bottleneck in reducing carbon emission in China's road transportation. New energy commercial vehicles are seen as an important way to reduce carbon emission in heavy commercial vehicles，but the market penetration rate of new energy commercial vehicles is much lower than that of other vehicle sectors. However，at present，the development of new energy zero-emission commercial vehicles still faces significant bottlenecks such as complex application scenarios，diversified technological paths，and high cost. This study constructs a Discrete Choice-based Market Evolution of Green Truck Model （DC-MEGT），a multi-dimensional Logit discrete choice model based on factors such as the total cost of ownership （TCO） and ease of use of new energy vehicles. TCO is calculated using a bottom-up approach，and the usage convenience is quantified and monetized by supplementary energy time cost. A comprehensive utility function is constructed to predict and analyze the market penetration rate evolution of different power types，such as pure electric vehicles，fuel cell vehicles，and zero-emission fuels from the present to 2060. The study analyzes the heavy-duty long-haul towing scenario as an example and finds that the main technology paths in 2060 include fuel cell vehicles，pure electric vehicles，natural gas vehicles，and diesel vehicles，accounting for 48%，28%，12%，and 10%，respectively. If the uncertainty of different factors such as policy promotion，technological progress，and business models is taken into account，the market share of pure electric vehicles and fuel cell vehicles in 2060 may fluctuate by 17% ~ 19%.

The wet clutch is the core component of the vehicle transmission system. It is prone to rub-impact between the friction plate and steel plate during high-speed separation，resulting in a sharp increase in drag torque，and affecting its transmission efficiency and reliability. Therefore，in this paper，to reduce the rub-impact drag torque in high-speed wet clutch，the micro-texture on the surface of the friction plate is optimally designed. Firstly，a parameterized modeling method of arbitrary micro-texture shape lines on the surface of friction plate is proposed. Then the number，depth，circumferential proportion，radial proportion and shape line parameters of the micro-texture are selected to construct the design variables，constraint conditions and optimal objective function for micro-texture optimization. By combining the experiment design method，approximation modeling simulation and global search optimization method，an optimal design model of micro-texture on the surface of friction plate is established. Finally，a comparison test of drag torque before and after micro-texture optimization is carried out. The results show that the optimized micro-texture can significantly reduce the rub-impact drag torque at high circumferential speed，and greatly delay the critical speed at which the rub-impact phenomenon of friction pair occurs.

The vibration and noise performance of the heat pump system plays an important role in the NVH evaluation of new energy vehicles. Based on the structure and working characteristics of the heat pump system and the principles of vehicle vibration and noise control，a research on the NVH control methods of the heat pump system is carried out in this paper from the vibration and noise excitation source，structural mode distribution，transfer path，evaluation conditions and other dimensions. Through the analysis and solution of NVH problems in the product development of a domestic hybrid electric car，the results indicate that the NVH control of heat pump system is a system engineering，and the compressor，air conditioning pipeline，HVAC shell，acoustic package and compressor control strategy are key factors of NVH，which provides a clear technical reference for the NVH performance control of new energy vehicle heat pump systems.

To improve the fuel economy of vehicles，simulation and experiments are combined to improve the aerodynamic drag coefficient during driving，taking a certain SUV model as the research object. Firstly，wind tunnel tests are used to determine the areas or components that have significant impact on the overall aerodynamic drag of the vehicle. Secondly，optimizations are made to the components or areas with high contribution values to the air resistance coefficient. The results show that the front wheel deflectors，taillights and spoilers contribute greatly to the overall air resistance coefficient of the vehicle. The restyling of the front wheel deflectors effectively reduces the frontal pressure area and interference drag from the wheels. Optimizations on taillights and spoilers improve the rear negative pressure zone and shorten the reattachment distance of separated flows on the upper part of the rear window. Based on the intrinsic orthogonal decomposition method for extracting and analyzing local flow field information，it can be concluded that the first and second order modals mainly constitute the key flow states in the wake. Compared to the initial scheme，a drag reduction rate of 7.5% can be achieved by the optimized combination design，which is verified by tests and simulations. Theoretical basis and technical support are provided in this paper for restyling and model change of the next generation of SUV.

For the difficulties in feature extraction and low recognition rate in defect types and grades of rivet on aluminum alloy plates for car body，the diagnosis model and detection method for rivet failure defects are proposed based on the Gaussian convolutional deep belief network and long short-term memory network. Firstly，the specimens are designed for five types of fracture defects and an automatic detection system is constructed. The planned path and pose of the probe are set to lower lift-off effect on signals. Secondly，the dual network fusion diagnostic model is designed to extract and learn the multi-dimensional defect feature information，solving the problem of extracting defect information represented by temporal variation characteristics and spatial distribution state in detection curves. The experiments results show that the optimized model has an average recognition rate of 99.85%，with an increase of 14.54% compared with that of the traditional convolutional network and single deep belief network. The model has better compatibility and robustness，which can realize online diagnosis of internal defects of rivets.

For the existing acquisition method of vehicle sideslip angle （VSA） based on fusion strategy，optimization and improvement are required for different scenarios，structures or signals. As a result，the calculation complexity and system cost rise up. A soft-sensing method for the VSA based on switch strategy is proposed in this paper. In the pretreatment part for sensor measurement signals，the Bessel filter is employed to realize the delay processing and noise filtering of lateral acceleration signal，and a reliability test module is designed to effectively eliminate the mutations in the signals of yaw rate，et al. On this basis，the switch strategy is determined based on the advantages of the existing kinematic and dynamic schemes. For the presented strategy，the continuous operating intervals of the kinematic scheme are shortened in a great deal of effort to restrain the error accumulation，and the dynamic one is restricted in linear region to avoid performance degradation. Simulations and hardware-in-loop experiments are implemented in multiple conditions to verify the effect of the proposed method. The experimental results show that the proposed method in this paper has obvious advantages in accuracy and execution time compared to the one utilizing the classical fusion strategy. Moreover，they are both robust to the change of road conditions.

A dual-motor non-synchronizer multi-gear mechanical transmission system can effectively improve the energy economy and power performance of heavy-duty commercial vehicles. In order to analyze the optimal performance of the system under the optimal parameters，and to consider the effect of vehicle weight and differences between no load and full load，this study optimizes both the drive motor parameters and mechanical transmission speed ratio parameters，and compares the energy economy and power performance of the single/dual-motor multi-gear mechanical transmission system under the optimal parameters. The results show that the dual-motor drive system reduces the sensitivity of the vehicle energy economy to the difference in vehicle weight and no/full load，with the maximum speed of the dual-motor drive system increased by about 8%，and the acceleration time saved by about 28%.