International Journal of Automotive Technology最新文献

Nonlinear Model Predictive Control (NMPC) is effective for local planning of automated vehicles, especially when there exist dynamical objects and multipe requirements. But it requires many computation resources for numerical optimization, which limits its practical application becase of the limited power of onboard unit. To extend the application range of the NMPC based local planner, the coupled nonlinear vehicle dynamics model is adopted based on the numerical analysis, which conversely requires much more discretization poits for acceptable accuracy. For better computation efficiency, Lagrange polynomials are used to discretize the vehicle dynamics model and objective function with less points and fine numerical accuracy. Furthermore, an adaptive strategy is designed to determine the order of Lagrange polynomials according to running state by numerical analysis of discretization error. Both acceleration effect and performance of the local planner designed by NMPC are validated by experimental tests under scenarios with multiple dynamical obstacles. The test results show that compared with the original one the accuracy and efficiency are improved by 74% and 60%, respectively.

In order to improve autonomous vehicles path-tracking accuracy and stability, a lateral–longitudinal coordination path-tracking control method is proposed. The proposed coordination control consists of path-tracking control and speed tracking control. First, the desired safety speed is planned according to the known road curvature and adhesion coefficient in order to prevent the tire force saturation. Based on the three-degree-of-freedom (3DOF) vehicle dynamic model and the preview tracking error model, model predictive control (MPC) theory is adopted to design the speed-varying vehicle path-tracking controller. Then, the quadratic programming (QP) method is used to solve the objective function with constraints, which calculates the steering angle to control the vehicle track the reference path. In addition, a PID speed controller is designed to calculate the torque of each wheel to track the desired speed. Finally, according to the yaw rate error and the vehicle slip angle error, a yaw moment stability controller based on the fuzzy logic control theory is designed to balance the vehicle stability and motility. The simulation results based on a Matlab/Carsim platform show that the coordination path-tracking control method proposed in this paper can effectively improve the vehicle tracking accuracy and the stability on different roads.

Water injection (WI) is a well-known technique to mitigate knocking phenomena, reducing the in-cylinder gas temperature with a high heat of vaporization and specific heat of water. In this study, the effect of WI directly into the cylinder on fuel efficiency was investigated using a 2.0 L naturally aspirated (NA), four-cylinder, port fuel injection (PFI)-spark-ignited (SI) engine. Spray visualization of water injection by a commercial gasoline direct-injection (GDI) injector was performed to elucidate the water evaporation characteristics. In engine experiments, combustion characteristics were analyzed by adjusting the WI timing and amount. Synergistic effects with other gas dilution techniques, such as EGR and Lean burn, were also investigated. The spray image of WI showed poor evaporation of water compared to gasoline, even at high fuel temperatures. The optimal timing of WI was advanced up to the early intake stroke due to the harsh conditions of NA engines for water evaporation compared to turbocharged engines. With the combination of EGR, the optimal WI timing was advanced by the compression stroke, and further fuel efficiency improvement was achieved. In lean combustion, WI can improve both combustion stability and fuel efficiency.

Aiming at the sensitivity problems of uncertain factors such as parameter variation, external disturbance and friction for the permanent magnet synchronous motor control system of electric vehicle, a fractional order complementary non-singular terminal sliding mode control method based on neural network is proposed. The mathematical model of permanent magnet synchronous motor with uncertain factors was established. The sliding mode controller was designed by combining the generalized sliding mode surface and the complementary sliding mode surface, which shortened the arrival time from the state trajectory to sliding mode surface. The fractional calculus operator with filtering characteristics was used to improve the position tracking accuracy and reduce the chattering. As for the variety of uncertain disturbances, the neural network was used to estimate the system total uncertainty and compensate online to further improve the dynamic response ability and anti-interference ability. Finally, the simulation results verify the effectiveness and feasibility of the proposed method, which can provide theoretical and technical support for improving the control accuracy of permanent magnet synchronous motor and the development of electric vehicles.

Abstract

In response to the climate crisis, nations are working to reduce emissions and improve energy efficiency, particularly in the transportation sector through the adoption of electric vehicles. However, the current official test methods for evaluating battery electric vehicle (BEV) energy economy and single-charge driving range are time-consuming, creating challenges for testing institutions and delaying the release of new models. The objective of this study is to compare the energy economy and single-charge driving range of BEVs using the different test methods, the full depleting test (e.g., multi cycle test (MCT), short multi cycle test, short multi cycle test plus) and partial depleting test (e.g., short process test (SPT)), with the aim of reducing the testing time on the chassis dynamometer. As a result of testing with three BEVs with different battery capacities, the test duration on the chassis dynamometer could be reduced by up to 85% compared to the MCT that is authorized test method by government. Each test has different repeatability, and SPT has a higher deviation from the MCT test results than other test methods. Overall, the study can provide reliable research outcomes conducive to the future improvement of official energy economy and single-charge driving range test standards for BEVs in each country.

The electrification of vehicles has become a major focus in the automotive industry due to worldwide efforts toward reducing carbon emissions and achieving sustainable mobility. However, a significant challenge in expanding electrified vehicle market is to address the issue of limited driving range, particularly in cold climates. Thus, a precise and reasonable model that integrates both the heating, ventilation, and air conditioning system and the battery thermal management system is necessary to systematically analyze the system performance at early development stage. Motivated by this, we developed an electric vehicle simulator that includes an integrated thermal management system and validated it by comparing with the real experimental data, and we have demonstrated the reliability of the developed model. Using the model, we could apply various control methods, e.g., PID, model predictive control, for tracking the reference cabin temperature under various driving environments. Our findings indicate that the simplified control-oriented model can be a reliable tool for various vehicle thermal control designs. We believe that this study can provide valuable insights into the design and optimization of the thermal management system of electrified vehicles.

To solve the problems of difficult quantification of complex driving scenes and unclear classification, a method of complex measurement and scene classification was proposed. Based on the Bayesian network, the posterior probability distribution was obtained, the variable weights were determined by information entropy theory and BP neural network, and the gravitational model was improved so that the complex metric model of the driving scene was established, the static and dynamic complexity of the scene was quantified respectively, and a weighted fusion of the two was conducted. The K-means clustering method was used to divide the driving scenario into three categories, i.e., simple scenario, medium complex scenario, and complex scenario, and the rationality of the method was verified by experiments. This scenario complex metric method can provide a reference for studying the complex metrics and scene classification of smart vehicle test scenarios.

Abstract

To improve the handling and directional stability of three-axle heavy vehicles, this paper suggests a control strategy that combines direct yaw moment control (DYC) and active front steering (AFS). The control system's structure is divided into three main layers. Based on an online adjustable index, a fuzzy controller acting as a supervised system decides the cooperation of DYC and AFS in the upper layer. In the intermediate layer, the DYC system controller uses a sliding mode controller to calculate the corrective body moment. The AFS system uses a fuzzy controller to generate the corrective steering angle necessary to achieve the three-axle vehicle motion objective. The algorithm for distributing braking force and the slip ratio control (SRC) system comprises the lower layer. The anti-lock braking system (ABS) in the SRC system is built to produce the necessary braking forces at low slip ratios while preventing the wheels from locking up at high slip ratios. Consideration has been given to a heavy, three-axle, 9-DOF nonlinear vehicle with uncertain dynamics. Trucksim software and simulation tests have validated the model. The proposed control system's satisfactory performance is shown through various maneuvers.

Abstract

The shape of the groove in the friction plate of a wet friction clutch has an influence on the dynamic friction coefficient of the friction pair. Some suggestions are put forward for the selection of the groove type of brake pads. This study establishes a dynamic friction coefficient calculation model for clutch engagement process considering the asperity and lubricant bearing capacities of the centrifugal force of the oil film. The model is based on the Reynolds equation, average flow model, and Greenwood model. The friction coefficients of different groove shapes were measured using the SAE#2 testing machine. The measured results were compared with theoretical calculations to verify the accuracy of the theoretical model. Under the premise of satisfying the torque transmission condition of the helicopter, the groove type of the wet clutch friction plate should be waffling groove or double arc groove. In this study, some suggestions are put forward for the selection of the groove type of the friction plate of the wet clutch.

Abstract

The Vehicle Dynamics Control (VDC) system is designed to enhance vehicle stability by effectively applying corrective yaw moments through differential brake forces during severe maneuvers. The VDC configuration primarily comprises two essential components: the supervisor and coordinators. The supervisor is responsible for determining appropriate corrective yaw moments, while the coordinators decide the tire forces necessary to achieve the desired corrective yaw moments. In modern times, various control schemes, such as model predictive controls, h-infinity controls, and relative controls, have been extensively investigated for the supervisors. However, in contrast, research concerning the coordinator component has not received much attention, resulting in relatively low research numbers. Most of the research has focused on the utilization of VDC coordinators that decide tire forces solely in proportion to corrective yaw moments. This approach leads to significant errors due to assumptions that do not account for the nonlinear characteristics of tires. In this research analysis, a coordinator considering nonlinear tire characteristics, such as the friction ellipse effect is presented. This crucial method of considering tire's nonlinear characteristics significantly enhances the accuracy of achieving the corrective yaw moment. Overall, the developed coordinator was validated through both simulations and experiments.