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A 3-D numerical analysis model of transient heat transfer among the multi-component coupling system in combustion chamber of internal combustion engine has been developed successfully in the paper. The model includes almost all solid components in combustion chamber, such as piston assembly, cylinder liner, cylinder head gasket, cylinder head, intake valves and exhaust valves, etc. With two different coupling heat transfer modes, one is the lubricant film heat conduction between two moving components, another is the contact heat conduction between two immovable solid components, and with the direct coupled-field analysis method of FEM, the heat transfer relation among the components is established. The simulation result dedicates the transient heat transfer process among the components such as moving piston assembly and cylinder liner, moving valves and cylinder head. The effect of cylinder head gasket on heat transfer among the components is also studied.

Electronic Stability Control (ESC) is an important measure to proactively guarantee vehicle safety. In this paper, the method of four-wheel hub-motor torque control is compared with the traditional single-wheel hydraulic brake control in ESC system. The control strategy adopts the hierarchical structure. In upper controller, the stability of the vehicle is identified by threshold method, the additional yaw moment control uses a way to get the moment including feedforward and feedback parts based on the linear quadratic regulator (LQR). The medium controller is tire slip rate control, in order to get the optimal target slip rate from the upper additional yaw moment, a method of quadratic programming to optimize the longitudinal force is proposed for each wheel. The inputs of tire state for the magic tire model is introduced so as to calculate the target slip rate from the target longitudinal force.

Taking full advantage of available traffic environment information, making control decisions, and then planning trajectory systematically under structured roads conditions is a critical part of intelligent vehicle. In this article, a lane-changing decision-making method for intelligent vehicle is proposed based on acceleration field. Firstly, an acceleration field related to relative velocity and relative distance was built based on the analysis of braking process, and acceleration was taken as an indicator of safety evaluation. Then, a lane-changing decision method was set up with acceleration field while considering driver’s habits, traffic efficiency and safety. Furthermore, velocity regulation was also introduced in the lane-changing decision method to make it more flexible.

An autonomous vehicle is a comprehensive intelligent system that includes environment sensing, vehicle localization, path planning and decision-making control, of which environment sensing technology is a prerequisite for realizing autonomous driving. In the early days, vehicles sensed the surrounding environment through sensors such as cameras, radar, and lidar. With the development of 5G technology and the Vehicle-to-everything (V2X), other information from the roadside can also be received by vehicles. Such as traffic jam ahead, construction road occupation, school area, current traffic density, crowd density, etc. Such information can help the autonomous driving system understand the current driving environment more clearly. Vehicles are no longer limited to areas that can be sensed by sensors. Vehicles with different autonomous driving levels have different adaptability to the environment.

A multitude of recent studies are suggestive of the EV as a paramount representative of the NEV, its development direction is transformed from “individuals adapt to vehicles” to “vehicles serve for occupants”. The multi-mode drive control technology is relatively mature in traditional auto control sphere, however, a host of EV continues to use a single control strategy, which lacks of flexibility and diversity, little if nothing interprets the vehicle performances. Furthermore, due to the complex road environment and peculiarity of vehicle occupants that different requirement has been made for vehicle performance. To solve above problems, this paper uses the key technology of mathematical statistics process in MATLAB, such as the mean, linear fitting and discrete algorithms to clean up, screening and classification the original data in general rules, and based on short trips in the segments of kinematics analysis method to establish a representative of quintessential driving cycle.

The earth's fossil energy is not limitless, and we should be taking advantage of the highly developed fields of science and technology to utilize it more efficiently and to create a fully environmentally friendly life. Considering the prodigious amount of vehicles in the world today, even a small improvement in their energy-saving performance could have a significant impact. In this paper, a new type of electro-hydraulic power steering (EHPS) system is described. It has two main advantages. First, it can significantly decrease the demand on the motor so that it can be used for a wider range of vehicles. Second, its pressure-flow characteristic can be programmed and is more flexible than hydraulic power steering (HPS) system. A prototype with a 500 W motor was applied to a truck with a front load of 2,700 kg, and static steer sweep tests were conducted to validate its feasibility.

In automatic driving application, the velocity planner can be considered as a key factor to ensure the safety and comfort. One of the most important tasks of the velocity planner is to simulate the velocity characteristics of human drivers. In this paper, two Driver In-the-Loop (DIL) experiments are designed to explain velocity characteristics of human drivers. In the first experiment, static obstacles are placed on both sides of the straight road to shorten the cross range that vehicles can driver across. Moreover, different cross ranges are set to study the influence of the steering wheel error. In the second experiment, velocity characteristics are investigated under the condition of different road widths and curvatures in a U-turn road contour. In both tests, different drivers’ preview behavior is analyzed through the operation of throttle, braking, and steering.

The RON(Research Octane Number) is the most important indicator of motor petrol, and the petrol refining process is one of the important links in petrol production. However, RON is often lost during petrol refining and RON Loss means the value of RON lost during petrol refining. The prediction of the RON loss of petrol during the refining process is helpful to the improvement of petrol refining process and the processing of petrol. The traditional RON prediction method relied on physical and chemical properties, and did not fully consider the high nonlinearity and strong coupling relationship of the petrol refining process. There is a lack of data-driven RON loss models. This paper studies the construction of the RON loss model in the petrol refining process.

In the present study, we developed a reduced chemical reaction mechanism consisted of n-heptane and toluene as surrogate fuel species for diesel engine combustion simulation. The LLNL detailed chemical kinetic mechanism for n-heptane was chosen as the base mechanism. A multi-technique reduction methodology was applied, which included directed relation graph with error propagation and sensitivity analysis (DRGEPSA), non-essential reaction elimination, reaction pathway analysis, sensitivity analysis, and reaction rate adjustment. In a similar fashion, a reduced toluene mechanism was also developed. The reduced n-heptane and toluene mechanisms were then combined to form a diesel surrogate mechanism, which consisted of 158 species and 468 reactions. Extensive validations were conducted for the present mechanism with experimental ignition delay in shock tubes and laminar flame speeds under various pressures, temperatures and equivalence ratios related to engine conditions.

Recovering the braking energy and reusing it can significantly improve the fuel economy of hybrid electric vehicles (HEVs).The battery ability of recovering electricity limits the improvement of the regenerative braking performance. As one way to solve this problem, the technology of brake-by-wire can be adopted in the HEVs to use the recovery dynamically. The use of high-power electrical equipment, such as electromechanical brake (EMB), is working in the form of brake-by-wire. Due to the nature of EMB, there exists an obvious coupling relationship between the energy flow and brake force distribution. In this paper, a brake force distribution controller is proposed in HEV with EMB, which can maximize braking energy recovery, compared with the conventional distribution control without EMB. Meanwhile, an energy flow strategy working with the distribution controller is designed, which is less limited to the performance of the battery.

This paper presents a study of LPG lean burn in a motorcycle SI engine. The lean burn limits are compared by several ways. The relations of lean burn limit with the parameters, such as engine speed, compression ratio and advanced spark ignition etc. are tested. The experimental results show that larger throttle opening, lower engine speed, earlier spark ignition timing, larger electrode gap and higher compression ratio will extend the lean burn limit of LPG. The emission of a LPG engine, especially on NOx emission, can be significantly reduced by means of the lean burn technology.

Using the nonlinear finite element analysis, three nonlinear characteristics of the rubber gasbag of the air spring on the bus are thoroughly analyzed, including the nonlinear characteristic of the rubber gasbag with multi layers of composite materials, the nonlinear large displacement geometry characteristic of the rubber gasbag on working, and the nonlinear contact characteristic of the rubber gasbag when contacts the pedestal and the top cover plate. A model is build and the nonlinear characteristic of the air spring on the bus is analyzed using the ABAQUS software. At last, the article discusses parameters that influence on the characteristic of the air spring for the bus.

Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

Turbochargers can improve vehicle dynamic performance and fuel economy and are applied widely nowadays. Due to the existence of turbocharger delay effect, acceleration delay and insufficient combustion are its disadvantages. By collecting high pressure gas which generates from the inertia of the turbine in the intake passage when the vehicle slows down, the gas can be supplied for the shortage while the vehicle is accelerating, which can reduce turbocharger delay effect directly. However, turbocharger delay effect changes a little at high speed and low speed which is subjected to the air inflation and short air-release time. This paper adds a set of pressure booster device on the existing inflating-deflating device, whose thermal energy comes from the compressed air and lubricating oil, to facilitate pressure increasing in inflating-deflating device and help the chamber change sooner, which avails to relieve the delay effect.

This paper presents a method of calculating temperature field of the piston by using a wavelet neural network (WNN) to identify the unknown boundary conditions. Because of the complexity of the heat transfer and limitations of experimental conditions of heat transfer analysis of the piston in a diesel engine, boundary conditions of the piston temperature field were usually obtained empirically, and thus the result itself was uncertain. By employing the capability of resolution analysis from a wavelet neural network, the method obtains improved boundary heat transfer coefficients with a limited number of measured temperatures. Using FEA software iteratively, results show the proposed wavelet neural network analysis method improves the prediction of unknown boundary conditions and temperature distribution consistent with the experimental data with an acceptable error.

This paper has designed a real time control algorithm to use ISG motor actively compensate the torque ripple produced by the engine, to reduce torsional vibration. This paper consists of 3 parts. In the first section, this paper has introduced the research object and its modification for experiments. Then the development of control strategy is presented. The engine dynamic model is built, and real-time control with a feedforward unit and a feedback unit is derived. Encoder and cylinder pressure is used for engine torque estimator. Then the ISG motor output the counter-waveform to make the overall output smooth. In order to verify the effectiveness of the control strategy, the final section has established a test bench, where two experiments are carried out. One of the experimental conditions is to set the engine at a constant operating point, while the other is to crank the engine from 0 rpm to idle speed with ISG motor.

For series hybrid electric vehicles (SHEV), rule-based strategies are realistic and powerful in real-time applications. However, the previous rule-based strategy cannot strike a balance between the best fuel economy and the best battery performance while maintaining the advantages of real-time applications. In order to obtain higher efficiency and reduce battery consumption, we have developed an adaptive hybrid thermostat strategy. On the basis of maintaining the load leveling of the thermostat strategy, the threshold-changing mechanism is added to realize the adaptive adjustment of the engine starting power under different SOC conditions, so as to achieve the goal of prolonging the battery life. In addition, the more fuel-efficient emergency handling rules designed to further reduce comprehensive fuel consumption.

Vehicles equipped with articulated steering systems have advantages such as low energy consumption, simple structure, and excellent maneuverability. However, due to the specific characteristics of the system, these vehicles often face challenges in terms of lateral stability. Addressing this issue, this paper leverages the precise and independently controllable wheel torques of a hub motor-driven vehicle. First, an equivalent double-slider model is selected as the dynamic control model, and the control object is rationalized. Subsequently, based on the model predictive control method and considering control accuracy and robustness, a weight-variable adaptive model predictive control approach is proposed. This method addresses the optimization challenges of multiple systems, constraints, and objectives, achieving adaptive control of stability, maneuverability, tire slip ratio, and articulation angle along with individual wheel torques during the entire steering process of the vehicle.

Numerical simulations on the fluid-structure interaction were conducted using commercial software STAR-CCM+ and ABAQUS. The aeroelastic responses of a deflector under several different working conditions were simulated utilizing finite volume and finite element methods to investigate the aeroelastic problem of automotive deflectors. Results showed that the structural response of a top deflector is minimal under the influence of aerodynamics given its large structural stiffness. The size of the top deflector was optimised by using thickness as a variable. The volume and quality of the top deflector were significantly reduced, and its lightweight performance was improved to satisfy the stiffness performance requirement. The vibration of a side deflector structure was mainly induced by the turbulence on the structure surface. The amplitude of vibration was small and the vibration gradually converged in a few seconds without obvious regularity.