For the fact that single control algorithm cannot simultaneously meet the requirements of autonomous vehicles for path tracking accuracy and controller solving speed, this paper proposed a hybrid control strategy based on Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC). The strategy used an LQR in the low-speed condition and an MPC algorithm in the high-speed condition, on the basis of which a switching mechanism of the control algorithm based on a Finite State Machine (FSM) was designed and the control parameters were optimized by Genetic Algorithm (GA). The hybrid control strategy was simulated and verified based on CarSim and MATLAB/Simulink simulation platforms, and the real vehicle test was further completed. The experimental results show that the designed hybrid control strategy can reduce the computation time on the basis of improving the tracking accuracy, and the average lateral error and average heading error are reduced by 26.3% and 39.6%, respectively, and the average computation time is reduced by 10.9% compared with the single control algorithm.

To clarify the limitations and development direction of the research on Collaborative Intersection Collision Warning (CICW), CICW research progress was reviewed systematically. Firstly, the advantages and disadvantages of the existing intersection traffic conflict detection methods were analyzed. Secondly, the applicability of different warning levels, mechanisms, and modes was summarized. Thirdly, the effectiveness and safety evaluation indexes of CICW were identified, and a comparison was made between simulation, real vehicle and virtual-real fusion testing. Then, the influence of driver uncertainty and unreliable communication on CICW and its optimization were analyzed. Finally, the future development direction of CICW was prospected. The results show that the traffic risk field model presents a feasible solution to solve the comprehensive characterization of risk and conflict severity in the existing CICW conflict detection methods. However, further research is needed to establish appropriate environmental parameters, risk indicators, and determination. Moreover, modeling, forecasting, and online identification of driver’s behavior in CICW application scenarios and the adaptive construction of CICW warning modes offer viable solutions to designing reliable and effective CICW applications. Achieving a comprehensive objective evaluation of CICW in all aspects depends on the research and establishment of a comprehensive evaluation mechanism and a large-scale experimental platform. The unreliable Internet Of Vehicle (IOV) communication seriously affects the effectiveness of CICW, so it is necessary to further study the channel congestion control mechanism and CICW fault-tolerant mechanism based on communication failure/failure prediction.

Based on the historical driving data of trucks in a province, this paper proposed a prediction method of dangerous driving behavior based on Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) network and self-attention mechanism. For the characteristics of large amount of truck driving data, high dimension, difficult feature extraction and strong time sequence, this method first used XGBoost to filter the features, then used CNN to extract spatial features and LSTM to further capture the temporal information of driving behaviors. Finally, dangerous driving behaviors were predicted by self-attention mechanism. Experimental results show that the method presented in this paper performs better than other long time series prediction methods on highway freight driving data in a province, with recognition accuracy reaching 85.05%, the weighted average recall rate reaches 83%, and the F1-score reaches 84%.

In order to solve the problem of low control accuracy and low parameter tuning efficiency caused by difficulty in selecting coefficient matrix Q and R of Linear Quadratic Regulator (LQR) in lateral control of intelligent vehicle, this paper proposed an optimization method of genetic particle mixing (Genetic Algorithm -Particle Swarm Optimization, GA-PSO). A lateral LQR controller and a feed-forward controller were designed based on the two-degree-of-freedom model of the vehicle. The coefficient matrix was optimized using the LQR controller’s own energy loss function as the cost function. The algorithm optimization results of GA-PSO and PSO were compared. The CarSim/Simulink co-simulation shows that the GA-PSO optimized controller improves the tracking accuracy and computing efficiency by 47.06% and 63.54%, respectively, and the optimized controller has strong robustness.

Based on the test platform of volume constant combustion bomb, the influence of geometrical parameters of the premixed single-orifice active pre-chamber on the ignition characteristics of the pre-chamber were investigated by the combustion visualization method. During the pressure constant combustion process in the early stage of flame development, the time from the start of ignition until the flame area reaches half of the visible window area of the combustion vessel is defined as the initial flame development time, which is used as a reference index to measure the ignition effect of the active pre-chamber under different geometrical parameters: under the test conditions of different orifice diameters (2.0~4.0 mm), different inner diameters of the pre-chamber channel (3.0~5.5 mm), and different open angles of the lower end (0°~75°), the maximal differences of initial flame development time are 9.3 ms, 6.8 ms, and 2.9 ms, respectively. Therefore, the effect of the three geometrical parameters on the ignition effect of the single-orifice active pre-chamber are, in descending order, the orifice diameter, the inner diameter of the pre-chamber channel and the opening angle of the lower end of the pre-chamber.

In order to improve the NVH performance of the timing housing of a gasoline engine specific for a range extender, several support bosses were added locally to the timing housing, which significantly improves the dynamic stiffness of the timing housing, and at the same time effectively reduces the vibration response and deformation per unit of excitation, so as to reduce the noise of the range extender assembly 1 m from the engine front-end side in the full-load acceleration condition by 4.0 dB(A), the linearity of the noise SPL and the acceleration of the vibration of the timing housing were significantly improved. The validation results show that improving the dynamic stiffness can effectively improve the noise radiation from the structural vibration of thin-walled parts.

In view of the trigger control and storage-recording in the process of automatic driving data collection, this paper started from advanced automatic driving data acquisition technology and advanced automatic driving storage technology, firstly investigated the sensor configuration methods of China and foreign automakers, then reviewed the automobile Event Data Recorder (EDR) system, autonomous driving data recording system and general L3 level autonomous vehicle data acquisition and storage schemes, and concluded that the existing data acquisition and storage technology could generate low quality and high noise redundant data. Finally, based on Tesla’s Shadow Mode, the paper introduced a driving data acquisition and storage method for man-machine co-driving mode, and summarized the development trend of advanced autonomous driving data acquisition technology.

To address combustion and emission issues in the lean combustion of gasoline direct injection (GDI) engine, ethanol-doped reformate gas was used to enhance the engine’s performance. The CONVERGE three-dimensional simulation technology was employed to explain the engine’s performance at a microscopic level. The results show that introducing ethanol-doped reformate gas can improve the distribution of equivalence ratio in the cylinder, promote the generation of H radicals and OH radicals, facilitating effective combustion. With an increase in the doping ratio of reforming gas, the distribution range and concentration of HO₂ and H₂O₂ become wider and higher, and the stratification phenomenon in the combustion chamber becomes more pronounced. As the doping ratio of reforming gas increases to 20%, the peak values of in-cylinder soot generation mass and number density are reduced by 90% and 56.25%, respectively, effectively improving the soot emissions of GDI engines.

To address the limitation that the traditional Automatic Emergency Braking(AEB) strategy based on Time To Collision (TTC) does not take into account the speed of the vehicle, this paper proposed a dynamic collision time threshold model that took into account the vehicle speed and an AEB control strategy based on dynamic collision time threshold was designed. In order to ensure the comfort and safety of the braking process, a two-stage braking strategy was determined and the deceleration rate was designed, using PI control to complete the vehicle deceleration control. The TTC thresholds for different vehicle speeds were determined through simulation and a dynamic crash time threshold model was established. Hardware-In-the-Loop (HIL) simulation results show that the AEB strategy designed in this paper improves the collision avoidance success rate by 47.6% compared with the traditional AEB strategy under the premise of ensuring comfort, thus has better comprehensive performance.

In order to improve the prediction accuracy of State Of Charge (SOC) of power batteries, this paper proposed a method to improve the traditional ampere-hour intergral method to estimate the SOC of the lithium-ion battery based on a single particle Li diffusion model. The solver programs for estimating SOC with traditional and improved ampere-hour integration method and communication interface programs for battery data acquisition were written in software LabVIEW, which achieved the on-line monitoring of the battery SOC under different environmental temperatures and currents by the two methods. The results show that, under the above discharging conditions, the maximum estimation errors of the improved method and the traditional ampere-hour integral method are 1.11% and 1.89%, respectively. When the discharge current changes dramatically, the battery SOC estimated by the improved method fluctuates less than the traditional ampere-hour integral method.