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During the launch of a car, severe torsional vibration sometimes may occur in its driveline due to somewhat the slipping of the clutch, its intuitive sense for an occupant is the longitudinal vibration of the vehicle, referred to as the launch shudder whose characteristic frequency is from 5 to 25 Hz generally. As the main vibration sources of the driveline and its crucial nonlinear components, the variable stiffness and backlash of the gear meshing are considered, their impacts on the launch shudder are analyzed in this paper. Conformal mapping, finite element method and regression method etc. are the main approaches to calculate the variable meshing stiffness of a gear pair. If this stiffness is get, it can usually be substituted for its approximate analytical expression, just with finite harmonic terms, in Fourier Series form into Ordinary Differential Equations(ODEs) to calculate the vehicle responses with its nonlinearity considered.

Environmental perception is a crucial subsystem in autonomous vehicles. In order to build safe and efficient traffic transportation, several researches have been proposed to build accurate, robust and real-time perception systems. Camera and LiDAR are widely equipped on autonomous self-driving cars and developed with many algorithms in recent years. The fusion system of camera and LiDAR provides state-of the-art methods for environmental perception due to the defects of single vehicular sensor. Extrinsic parameter calibration is able to align the coordinate systems of sensors and has been drawing enormous attention. However, differ from spatial alignment of two sensors’ data, joint calibration of multi-sensors (more than two sensors) should balance the degree of alignment between each two sensors.

Lithium-ion batteries (LIBs) with relatively high energy, power density and eco-friendly characteristic are considered as a vital energy source in consumer market of portable electronics and transportation sector especially in electric vehicles (EVs). To meet the higher capacity requirements, the nickel-rich LIBs with higher capacity has been used as the commercial power batteries. However, the battery with higher energy density is more destructive, which could result in thermal runaway accidents and make the battery safety issues become more and more prominent. Thermal runaway of LIBs is one of the key scientific problems in safety issues. Until now, the inducement of thermal runaway process is complicated which perplex researchers and industry a lot. On the one hand, the internal mechanism about thermal runaway should be deeply studied. On the other hand, in-situ monitoring should be developed to supply the mechanism study and early warning.

Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines.

Recently, electro-hydraulic brake systems (EHB) has been developed to take place of the vacuum booster, having the advantage of faster pressure build-up and continuous pressure regulation. In contrast to the vacuum booster, the pressure estimation for EHB is worth to be studied due to its abundant resource (i.e. electric motor) and cost-effective benefit. This work improves an interconnected pressure estimation algorithm (IPEA) based on actuator characteristics by introducing the vehicle dynamics and validates it via vehicle tests. Considering the previous IPEA as the prior pressure estimation, the wheel speed feedback is used for modification via a proportional-integral (PI) observer. Superior to the IPEA based on actuator characteristics, the proposed PEA improves the accuracy by more than 20% under the mismatch of pressure-position relation.

In order to explore approaches for improving object detection accuracy in intelligent vehicle system, we exploit super-resolution techniques. A novel method is proposed to confirm the conjecture whether some popular super-resolution networks used for environmental perception of intelligent vehicles and robots can indeed improve the detection accuracy. COCO dataset which contains images from complex ordinary environment is utilized for the verification experiment, due to it can adequately verify the generalization of each algorithm and the consistency of experimental results. Using two representative object detection networks to produce the detection results, namely Faster R-CNN and YOLOv3, we devise to reduce the impact of resizing operation. The two networks allow us to compare the performance of object detection between using original and super-resolved images. We quantify the effect of each super-resolution techniques as well.

Whole field displacement/strain measurement of automotive components can be done efficiently by digital image correlation based technique. Inverse problems with this kind of input data, such as the identification of damage parameters/effective modulus in different part of a component, can be pursued by either virtual fields method or finite element model updating. In this paper, the two methods are applied to the identification of a tension plate with a circular hole, and different aspects of the two methods are discussed. It is found that the success of virtual fields method relies on the choice of a set of optimal virtual displacement fields; finite element model updating, on the other hand, can be applied to any geometry and any load condition, and can also be applied to problems where only limited number of measurements are available. However, its performance relies on the choice of optimization algorithms.

Laser cladding is a novel process of surface coating, and researchers in both academia and industry are developing additive manufacturing solutions for large, metallic components. There are many interlinked process parameters associated with laser cladding, which may have an impact on the resultant microhardness profile throughout the bead zone. A set of single bead laser cladding experiments were done using a 4 kW fiber laser coupled with a 6-axis robotic arm for 420 martensitic stainless steel powder. A design of experiments approach was taken to explore a wide range of process parameter settings. The goal of this research is to determine whether robust predictive models for hardness can be developed, and if there are predictive trends that can be employed to optimize the process settings for a given set of process parameters and microhardness requirements.

Path following controller of a six-wheel skid-steering vehicle is designed. The vehicle speed is controlled through engine speed control and the lateral vehicle steering is controlled through hydraulic braking on each side. Contrary to the common approaches considering non-holonomic constraints, vehicle dynamic characteristics and nonlinear characteristics of tire are considered. A hierarchical control structure is applied in this vehicle control system. The kinematic controller works out the reference yaw rate and reference vehicle speed. And a robust dynamic controller tracks the reference signal. In addition, the dynamic controller takes actuator ability into account.

Boosting and downsizing is the trend of future gasoline engine technology. For the turbocharged engines, the actuation of intake boosting pressure is very important to the performance output. In this paper, a GT-Power simulation model is built based on a 1.5 L turbocharged gasoline engine as the research object. The accuracy of model has been verified through the bench test data. Then it is conducted with numerical simulation to analyze the effect of wastegate diameter on the engine performance, including power output and fuel economy. Mainly the wastegate diameter is optimized under full engine operating conditions. Finally an optimal MAP of wastegate diameter is drawn out through interpolation method. By the transmission relationship between wastegate and actuator, a wastegate control MAP for electric actuated wastegate can be obtained.

For sensing system, the trustworthiness of the variant sensors is the crucial point when dealing with advanced driving assistant system application. In this paper, an approach to a hybrid camera-radar application of vehicle tracking is presented, able to meet the requirement of such demand. Most of the time, different types of commercial sensors available nowadays specialize in different situations, such as the ability of offering a wealth of detailed information about the scene for the camera or the powerful resistance to the severe weather for the millimeter-wave (MMW) radar. The detection and tracking in different sensors are usually independent. Thus, the work here that combines the variant information provided by different sensors is indispensable and worthwhile. For the real-time requirement of merging the measurement of automotive MMW radar in high speed, this paper first proposes a fast vehicle tracking algorithm based on image perceptual hash encoding.

Electromechanical Braking System (EMB) stops the wheel by motor and related enforce mechanism to drive braking pads to clamp the friction plate. It is compact in sized as well as faster in response, which solves the issue of potential leakage and slows response of traditional hydraulic brake system. The institutions at home and abroad have put forward all kinds of new structural schemes of EMB. At present, there are various EMB structural schemes, but the analysis and evaluation of these schemes are relatively few. In this paper, on the basis of a large number of research, the EMB actuator is modular decomposed according to function ,then the parametric 3D model library of each function module is established. According to brake requirements of the target vehicle, a development platform is set up to match EMB actuator structure scheme quickly.

Traditional active suspension which is equipped with hydraulic actuator or pneumatic actuator features slow response and high power consumption. However, electromagnetic actuated active suspension benefits quick response and energy harvesting from vibration at the same time. To design a novel active and energy regenerative suspension (AERS) utilizing electromagnetic actuator, this paper investigates the benchmark cars available on the market and summaries the suspension features. Basing on the investigation, a design reference for AERS design is proposed. To determine the parameters of the actuator, a principle is proposed and the parameters of the actuator are designed accordingly. Compared the linear type and rotary type Permanent Magnet Synchronous Motor (PMSM), the rotary type is selected to construct the actuator of the AERS. Basing on the suspension structure of the design reference model and utilizing rotary type PMSM, a novel AERS structure is proposed.

Faced with intricate traffic conditions, the single sensor has been unable to meet the safety requirements of Advanced Driver Assistance Systems (ADAS) and autonomous driving. In the field of multi-target tracking, the number of targets detected by vision sensor is sometimes less than the current tracks while the number of targets detected by millimeter wave radar is more than the current tracks. Hence, a multi-sensor information fusion algorithm is presented by utilizing advantage of both vision sensor and millimeter wave radar. The multi-sensor fusion algorithm is based on centralized fusion strategy that the fusion center takes a unified track management. At First, vision sensor and radar are used to detect the target and to measure the range and the azimuth angle of the target. Then, the detections data from vision sensor and radar is transferred to fusion center to join the multi-target tracking with the prediction of current tracks.

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.

A specially designed generator has been developed to produce poly-disperse droplet streams: A liquid fuel (n-heptane) is metered to an ultrasonic atomizer to produce droplets, which are then carried and accelerated vertically upwards through a nozzle tube by carrier-air flow. Conditions of the streams at the nozzle exit are modulated by varying the length of nozzle tubes, the fuel and carrier-air flow rate. Optical measurement techniques such as direct photography method, schlieren photography and particle image velocimetry (PIV) are employed to characterize its performance characteristics. Effects of the nozzle tube length, the carrier-air and fuel flow rate are investigated to evaluate the performance of the generator. Longer nozzle tubes provide a better flow guidance for the carrier-air, and tend to generate streams with less and smaller droplets due to the transporting losses.

Alumina (Al2O3) thin film coatings are applied on Al alloys using Plasma Electrolytic Oxidation (PEO) method to reduce the wear and corrosion problems. Plasma Electrolytic Aluminating (PEA) is a technique which could generate Alumina coatings on cast iron, mild steel and copper alloys. In this study, the aim is to explore the anti-wear and anti-corrosion behaviours of PEA Alumina coatings on gray cast iron. The dry sliding tribology test data was obtained from Pin-on-Disk (POD) tests against SAE 52100 steel and Tungsten Carbide (WC) counterfaces. Comparing with the PEO Alumina coatings, the PEA Alumina coating has much lower Coefficient of Friction (COF) and less wear. The microstructure, chemical composition and phase composition of this coating were investigated with Scanning Electron Microscope (SEM), Energy-Dispersive X-Ray Spectroscopy (EDX) and X-Ray Diffraction (XRD), respectively. There was FeO (or FeAl2O4) found on the PEA Alumina coating.

Indirect rotary transducer for an automotive screen interface is an innovative solution for the smart cockpit. The primary objective of this study is to design an indirect rotary transducer system, and study its feasibility in the smart cockpit. The working theory of this designed system is that the magnetic induction hall electronic chip can detect changes in the magnetic field. Several tests have been conducted, which show that the hypothesis of dangling operating system achieves the same effect as a hard-wired operating system. The results of the experiment indicate that the magnetic induction hall sensor can meet the specification of traditional hard-wired operating system. This system is a good concept for intelligent cab driving, which can fully meet the needs of the current market.

In this study, effects of altitude on free diesel spray morphology, macroscopic spray characteristics and air-fuel mixing process were investigated. The diesel spray visualization experiment using high-speed photography was performed in a constant volume chamber which reproduced the injection diesel-like thermodynamic conditions of a heavy-duty turbocharged diesel engine operating at sea level and 1000 m, 2000 m, 3000 m and 4500 m above sea level. The results showed that the spray morphology became narrower and longer at higher altitude, and small vortex-like structures were observed on the downstream spray periphery. Spray penetration increased and spray angle decreased with increasing altitude. At altitudes of 0 m, 1000 m, 2000 m, 3000 m and 4500 m, the spray penetration at 1.45 ms after start of injection (ASOI) were 79.54 mm, 80.51 mm, 81.49 mm, 83.29 mm and 88.92 mm respectively, and the spray angle were 10.9°, 10.8°, 10.7°, 10.4°and 9.8° respectively.

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.