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Exhaust gas recirculation technology is one of the main methods to reduce engine emissions. The pressure of the intake pipe of turbocharged direct-injection diesel engine is high, and it is difficult to realize EGR technology. The application of Venturi tube can easily solve this problem. In this paper, the working principle of guide-injection Venturi tube is introduced, the EGR system and structure of a turbocharged diesel engine using the guide-injection Venturi tube are studied. According to the working principle of EGR system of turbocharged diesel engine, the model of guide-injection Venturi tube is established, the calculation grid is divided, and it is carried out by using Computational Fluid Dynamics method that the three-dimensional numerical simulation of the internal flow of Venturi tube under different EGR rates injection.

SLAM (Simultaneous Localization and Mapping) plays a key role in autonomous driving. Recently, 4D Radar has attracted widespread attention because it breaks through the limitations of 3D millimeter wave radar and can simultaneously detect the distance, velocity, horizontal azimuth and elevation azimuth of the target with high resolution. However, there are few studies on 4D Radar in SLAM. In this paper, RI-FGO, a 4D Radar-Inertial SLAM method based on Factor Graph Optimization, is proposed. The RANSAC (Random Sample Consensus) method is used to eliminate the dynamic obstacle points from a single scan, and the ego-motion velocity is estimated from the static point cloud. A 4D Radar velocity factor is constructed in GTSAM to receive the estimated velocity in a single scan as a measurement and directly integrated into the factor graph. The 4D Radar point clouds of consecutive frames are matched as the odometry factor.

Multi-Target tracking is a central aspect of modeling the surrounding environment of autonomous vehicles. Automotive millimeter-wave radar is a necessary component in the autonomous driving system. One of the biggest advantages of radar is it measures the velocity directly. Another big advantage is that the radar is less influenced by environmental conditions. It can work day and night, in rainy or snowy conditions. In the expressway scenario, the forward-looking radar can generate multiple objects, to properly track the leading vehicle or neighbor-lane vehicle, a multi-target tracking algorithm is required. How to associate the track and the measurement or data association is an important question in a multi-target tracking system. This paper applies the nearest-neighbor method to solve the data association problem and uses an extended Kalman filter to update the state of the track.

An electrochemical impedance spectroscopy battery model based on the porous electrode theory is used in the paper, which can comprehensively depict the internal state of the battery. The effect of battery key parameters (the radius of particle, electrochemical reaction rate constant, solid/electrolyte diffusion coefficient, conductivity) to the simulated impedance spectroscopy are discussed. Based on the EIS analysis, a lithium-ion battery optimized equivalent circuit model is built. The parameters in the equivalent circuit model have more clear physical meaning. The reliability of the optimized equivalent circuit model is verified by compared the model and experiments. The relationship between the external condition and internal resistance could be studied according to the optimized equivalent circuit model. Thus the internal process of the power battery is better understood.

As a critical technology for autonomous vehicles, high precise positioning is essential for automated container terminals to implement intelligent dispatching and to improve container transport efficiency. Because of the unstable performance of global positioning system (GPS) in some circumstances, an ultra wide band (UWB) positioning system is developed for autonomous trucks in an automated container terminal. In this paper, an asynchronous structure is adopted in the system, and a three-dimensional (3D) localization method is proposed. Other than a traditional UWB positioning system with a server, in this asynchronous system, positions are calculated in the vehicle. Therefore, propagation delays from the server to vehicles are eliminated, and the real-time performance can be significantly improved. Traditional 3D localization methods based on time difference of arrival (TDOA) are mostly invalid with anchors in the same plane.

Battery models are often applied to describe the dynamic characteristics of batteries and can be used to predict the state of the battery. Due to the process of charging and discharging, the battery heat generation will cause the inhomogeneity between inner battery temperature and surface temperature. In this paper, a novel battery impedance model, which takes the impact of the battery internal temperature gradient on battery impedance into account, is proposed to improve the battery model performance. Several experiments are designed and conducted for pouch typed battery to investigate the electrochemical impedance spectroscopy (EIS) characteristics with the artificial temperature gradient (using a heating plate). Experimental results indicate that the battery internal temperature gradient will influence battery EIS regularly.

Positioning system is a key module of autonomous driving. As for LiDAR SLAM system, it faces great challenges in scenarios where there are repetitive and sparse features. Without loop closure or measurements from other sensors, odometry match errors or accumulated errors cannot be corrected. This paper proposes a construction method of LiDAR anchor constraints to improve the robustness of the SLAM system in the above challenging environment. We propose a robust anchor extraction method that adaptively extracts suitable cylindrical anchors in the environment, such as tree trunks, light poles, etc. Skewed tree trunks are detected by feature differences between laser lines. Boundary points on cylinders are removed to avoid misleading. After the appropriate anchors are detected, a factor graph-based anchor constraint construction method is designed. Where direct scans are made to anchor, direct constraints are constructed.

Autonomous driving related technologies have become a hot topic in academia and industry. Planning control is one of the core technologies of autonomous driving, which is conducive to vehicles safe and efficient driving. This paper proposes a novel optimal speed control algorithm, which considers the power system's energy consumption, the speed limit on the road, and the safe distance of the vehicle in front. An optimal speed control model of “From battery to wheel” energy consumption is established by constructing a performance index function based on the best-fitting formula of motor power, motor speed and torque. Based on the optimal control principle, the fourth-order ordinary differential equation of the speed control model is established, based on the indirect adjoining approach, the speed control model under the restriction of the road speed limit and safe distance of the preceding vehicle is derived and the analytical expression is obtained.

With the popularity of automated vehicles, the future mixed traffic flow contains automated vehicles with different degrees of intelligence developed by other manufacturers. Therefore, simulating the interaction behavior of automated vehicles with varying levels of intelligence is crucial for testing and evaluating autonomous driving systems. Since the algorithm of traffic vehicles with various intelligence levels is difficult to obtain, it leads to hardships in quantitatively characterizing their interaction behaviors. Therefore, this paper designs a new automated vehicle test platform to solve the problem. The intelligent vehicle testbed with multiple personalized in-vehicle control units in the loop consists of three parts: 1. Multiple controllers in the loop to simulate the behavior of traffic vehicles；2. The central console applies digital twin technology to share the same traffic scenario between the tested vehicle and the traffic vehicle, creating a mixed traffic flow. 3.

Automated driving system is a multi-source sensor data fusion system. However different type sensor has different operating frequencies, different field of view, different detection capabilities and different sensor data transition delay. Aiming at these problems, this paper introduces the processing mechanism of out of sequence measurement data into the multi-target detection and tracking system based on millimeter wave radar and camera. After the comparison of ablation experiments, the longitudinal and lateral tracking performance of the fusion system is improved in different distance ranges.

As one of the key technologies in autonomous driving, the lateral planning module guides the lateral movement during the driving process. An integrated lateral planning module should consider the non-holonomic constraints of a vehicle, the optimization of the generated trajectory and the applicability to various scenarios. However, the current lateral planning methods can only meet parts of these requirements. In order to satisfy all the performance requirements above, a novel Potential Field (PF) based lateral planning method is proposed in this paper. Firstly, a PF model is built to describe the potential risk of the traffic entities, including the obstacles, road boundaries and lines. The potential fields of these traffic entities are determined by their properties and the traffic regulations. Secondly, the planning algorithm is presented, which comprises three modules: state prediction, state search and trajectory generation.

With increasing pressure from environment problem for reduction in CO2 emissions and stricter fuel targets from road vehicles, new transmission technologies are gaining more attention in different main market. To get suitable road load data for transmission durability development is becoming increasingly important and can shorten the development time of new transmission. This paper presents the procedure and methods of road load data development for durability design of transmission product and optimization based on the real road data measurement, statistical characteristics evaluation and fatigue damage equivalency. Apply this road load data method procedure on 3 type of vehicle which represent conventional vehicle, BEV and HEV.

A rapid path-planning algorithm that generates drivable paths for an autonomous vehicle operating in structural road is proposed in this paper. Cubic B-spline curve is adopted to generating smooth path for continuous curvature and, more, parametric basic points of the spline is adjusted to controlling the curvature extremum for kinematic constraints on vehicle. Other than previous approaches such as inverse kinematics, model-based prediction postprocess approach or closed-loop forward simulation, using the kinematics model in each iteration of path for smoothing and controlling curvature leading to time consumption increasing, our method characterized the vehicle curvature constraint by the minimum length of segment line, which synchronously realized constraint and smooth for generating path. And Differ from the path of robot escaping from a maze, the intelligent vehicle traveling on road in structured environments needs to meet the traffic rules.

The effectiveness of after-treatment systems depends on the exhaust gas temperature, which is low during cold-start. As a result, Euro III, Euro IV and FTP75 require that the emissions tests include exhaust from the beginning of cold start. It is proved that 50%∼80% of HC and CO emissions are emitted during the cold start and the amount of unburned fuel from the crevices during starting is much higher than that under warmed engine conditions. The piston crevices is the most part of combustion chamber crevices, and results of mathematical simulations show that the piston crevice contribution to HC emissions is expected to increase during cold engine operation. Based on the transient HC test data and the double zone combustion model, this paper presents the study of the crevice HC Mechanism of the first firing cycle at cold start on an LPG SI Engine. A fast-response flame ionization detector (FFID) was employed to measure transient HC emissions of the first firing cycle.

Image corruptions due to noise, blur, contrast change, etc., could lead to a significant performance decline of Deep Neural Networks (DNN), which poses a potential threat to DNN-based autonomous vehicles. Previous works attempted to explain corruption from a Fourier perspective. By comparing the absolute Fourier spectrum difference between corrupted images and clean images in the RGB color space, they regard the noise from some corruptions (Gaussian noise, defocus blur, etc.) as concentrating on the high-frequency components while others (contrast, fog, etc.) concentrate on the low-frequency components. In this work, we present a new perspective that unifies corruptions as noise from high frequency and thus propose an image augmentation algorithm to achieve a more robust performance against common corruptions. First, we notice the 1/fα statistical rule of the natural image's spectrum and the channels-wise differential sensitivity on the YCbCr color space of the Human Visual System.

Combustion diagnostics of highly diluted mixtures are essential for the estimation of the combustion quality, and control of combustion timing in advanced combustion systems. In this paper, a novel fast response flame detection technique based on active plasma is introduced and investigated. Different from the conventional ion current sensing used in internal combustion engines, a separate electrode gap is used in the detecting probing. Further, the detecting voltage across the electrode gap is modulated actively using a multi-coil system to be slightly below the breakdown threshold before flame arrival. Once the flame front arrives at the probe, the ions on the flame front tend to decrease the breakdown voltage threshold and trigger a breakdown event. Simultaneous electrical and optical measurements are employed to investigate the flame detecting efficacy via active plasma probing under both quiescent and flow conditions.

The vibration characteristics of hybrid vehicles are very different from that of traditional fuel vehicles. In this paper, the active and passive control schemes are used to inhibit the vibration issues in vehicle hybrid powertrain system. Firstly the torsional vibration mechanical model including engine, motor and planetary gear subsystems is established. Then the transient vibration responses of typical working condition are analyzed through power control strategy. Consequently the active and passive control of torsional vibration in hybrid powertrain system is proposed. The active control of the motor and generator torque is designed and the vehicle longitudinal vibration is reduced. The vibration of the planetary gear system is ameliorated with passive control method by adding torsional vibration absorbers to power units. The vibration characteristics in vehicle hybrid powertrain system are effectively improved through the active and passive control.

Manufacturers have been encouraged to accommodate advanced downsizing technologies such as the Variable Displacement Engine (VDE) to satisfy commercial demands of comfort and stringent fuel economy. Particularly, Active control engine mounts (ACMs) notably contribute to ensuring superior effectiveness in vibration attenuation. This paper incorporates a PID controller into the active control engine mount system to attenuate the transmitted force to the body. Furthermore, integrated time absolute error (ITAE) of the transmitted force is introduced to serve as the control goal for searching better PID parameters. Then the particle swarm optimization (PSO) algorithm is adopted for the first time to optimize the PID parameters in the ACM system. Simulation results are presented for searching optimal PID parameters. In the end, experimental validation is conducted to verify the optimized PID controller.

Harmony-with-traffic refers to the ability of autonomous vehicles to maximize the driving benefits such as comfort, efficiency, and energy consumption of themselves and the surrounding traffic during interactive driving under traffic rules. In the test of harmony-with-traffic, one or more background vehicles that can respond to the driving behavior of the vehicle under test are required. For this purpose, the functional requirements of car-following model for harmony-with-traffic evaluation are analyzed from the dimensions of test conditions, constraints, steady state and dynamic response. Based on them, an interactive car-following model (ICFM) is developed. In this model, the concept of equivalent distance is proposed to transfer lateral influence to longitudinal. The calculation methods of expected speed are designed according to the different car-following modes divided by interaction object, reaction distance and equivalent distance.

An online fault detection and isolation (FDI) method for several common sensor faults and even demagnetization of PMSM is proposed by combining model-based and signal analysis technology. To begin with, the field reconstruction method (FRM) of PMSM is employed to obtain the flux residuals which are used as the criterion of fault detection. Then, the flux residuals are transformed by multi sequence harmonic synchronous rotating transformation and inputted into low pass filters (LPFs) in order to obtain the DC components. Last, offset and gain faults of the two phase current sensors, offset fault of the rotor angle sensor and permanent magnet (PM) demagnetization can be isolated by comparing the DC components and preset thresholds. The detection and isolation strategy of PMSM is validated by motor controller hardware in motor bench tests.