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High speed on-off valves (HSVs) are widely used in advanced hydraulic braking actuators, including regenerative braking systems and active safety systems, which take crucial part in improving the energy efficiency and safety performance of vehicles. As a component involving multiple physical fields, the HSV is affected by the interaction of the fields-fluid, electromagnetic, and mechanical. Since the opening of the HSV is small and the flow speed is high, cavitation and vortex are inevitably brought out so that increase the valve’s noise and instability. However, it is costly and complex to observe the flow status by visual fluid experiments. Hence, in this article a visual multi-physics system simulation model of the HSV is explored, in which the flow field model of the HSV built by computational fluid dynamic (CFD) is co-simulated with the model of hydraulic actuator established by AMESim.

It is very significant for autonomous vehicles to have the ability to operate beyond the stable handling limits, which plays a vital role in vehicles’ active safety and enhances riding and driving pleasure. For traditional vehicles, it is rather difficult to control the longitudinal speed, sideslip angle and yaw rate simultaneously when drifting along a given trajectory because they are under-actuated. Nevertheless, for a 4-wheel-independent-drive (4WID) vehicle, it is possible and controllable thanks to its over-actuated characteristics. This article designs a trajectory following control strategy for automated drifting of 4WID vehicles. First, a double-track 7 degree of freedom (7DOF) vehicle dynamic model is established, which incorporates longitudinal and lateral load transfer and considers nonlinear tire models. The controller which proposes a hierarchical architecture is then designed.

Special purpose flat-bed vehicle is commonly utilized to move heavily items such as containers in warehouse, port and other freight handling scene, the hydraulic steering system have be gradually replaced by electric ones. However, the cost of electric steering system is high for commercial activities. Thus, for some corporates, the differential braking steering strategy becomes an ideal alternative. The purpose of this paper is to present a steering control method for flat-bed electric vehicle based on differential braking system. There are two main components of the control method, steering while moving forward and pivot steering, and each of them was composed by upper layer and executive layer. To evaluate the practicability of the control methods, a 7-DOF flat-bed vehicle model was established in Simulink.

Advanced exhaust after-treatment technology is required for heavy-duty diesel vehicles to achieve stringent Euro VI emission standards. Diesel particulate filter (DPF) is the most efficient system that is used to trap the particulate matter (PM), and particulate number (PN) emissions form diesel engines. The after-treatment system used in this study is catalyzed DPF (CDPF) downstream of diesel oxidation catalyst (DOC) with secondary fuel injection. Additional fuel is injected upstream of DOC to enhance exothermal heat which is needed to raise the CDPF temperature during the active regeneration process. The objective of this research is to numerically investigate soot loading and active regeneration of a CDPF on a heavy-duty diesel engine. In order to improve the active regeneration performance of CDPF, several factors are investigated in the study such as the effect of catalytic in filter wall, soot distribution form along filter wall, and soot loads.

The strategy for emission reduction in the P2.5 hybrid system involves the optimization of engine torque, engine speed, catalyst heat duration, and motor torque regulation in a coordinated manner. In addition to employing traditional engine control methods used in HEV models, unique approaches can be utilized to effectively manage emissions. The primary principle is to ensure that the engine operates predominantly under steady-state conditions or limits its load to regulate emissions levels. The main contributions of this paper are as follows: The first is the optimization of catalyst heating stage. During the catalyst heating stage, the system divides it into one or two stages. In the first stage, the vehicle is driven by the motor while keeping the engine idle. This approach stabilizes catalyst heating and prevents fluctuations in air-fuel ratio caused by speed and load changes that could potentially worsen emissions performance.

Diesel particulate filter (DPF) is necessary for diesel engines to meet the increasingly stringent emission regulations. Many studies have demonstrated that the lubricant derived ash has a significant effect on DPF pressure drop and engine fuel economy, and this effect becomes more and more severe with the increasing of operating hours of the DPF because the ash accumulated in the DPF cannot be removed by regeneration. It is reported that most of the DPFs operated with more ash than soot in the filter for more than three quarters of the time during its lifetime [1]. In order to mitigate this problem, the original engine manufacturers (OEM) tend to use an oversized DPF for the engine. However, it will increase the costs of the DPF and reduce the compactness of the engine aftertreatment system.

Multibody human models are widely used to investigate responses of human during an automotive crash. This study aimed to validate a commercially available multibody human body model against response corridors from volunteer tests conducted by Naval BioDynamics Laboratory (NBDL). The neck model consisted of seven vertebral bodies, and two adjacent bodies were connected by three orthogonal linear springs and dampers and three orthogonal rotational springs and dampers. The stiffness and damping characteristics were scaled up or down to improve the biofidelity of the neck model against NBDL volunteer test data because those characteristics were encrypted due to confidentiality. First, sensitivity analysis was performed to find influential scaling factors among the entire set using a design of experiment.

A novel fault tolerant brake strategy for In-wheel motor driven electric vehicles based on integral sliding mode control and optimal online allocation is proposed in this paper. The braking force distribution and redistribution, which is achieved in online control allocation segment, aim at maximizing energy efficiency of the vehicle and isolating faulty actuators simultaneously. The In-wheel motor can generate both driving torque and braking torque according to different vehicle dynamic demands. In braking procedure, In-wheel motors generate electric braking torque to achieve energy regeneration. The strategy is designed to make sure that the stability of vehicle can be guaranteed which means vehicle can follow desired trajectory even if one of the driven motor has functional failure.

The diesel particulate filter (DPF) is an effective technology for particulate matter (PM) and particle number (PN) reduction. On heavy-duty diesel engines, the passive regeneration by Diesel Oxidation catalysts (DOC) and catalyzed DPFs (CDPF) is widely used for its simplicity and low cost, which is generally combined with the active regeneration of exhaust fuel injection. This study investigated a DOC-CDPF system with exhaust fuel injection upstream of the DOC. The system was integrated with a 7-liter diesel engine whose engine-out PM emission was below the Euro IV level and tested on an engine dynamometer. PM and PN concentrations were measured based on the Particle Measurement Programme (PMP), and the number/size spectrum for particles was obtained by a Differential Mobility Spectrometer (DMS). The filtration efficiency of DPF on PN was higher than 99% in ESC test, while the efficiency on PM was only 58%.

Diesel particulate filter (DPF) is indispensable for diesel engines to meet the increasingly stringent emission regulations. Both the peak temperature and the maximum temperature gradient of the DPF during active regeneration should be well controlled in order to enhance the reliability and durability of the filter. In this paper, the temperature field of the DPF during active regeneration with hydrocarbon (HC) injection was investigated with engine bench tests and numerical simulation. For the experimental study, 24 thermocouples were inserted into the DPF channels to measure the inner temperature of the filter to capture its temperature field, and the circumferential, axial and radial distribution of the filter temperature was analyzed to understand the DPF temperature field behavior during active regeneration.

Gasoline particulate filter (GPF) is considered a suitable solution to meet the increasingly stringent particle number (PN) regulations for both gasoline direct injection (GDI) and multi-port fuel injection (MPI) engines. Generally, GDI engines emit more particulate matter (PM) and PN. In recent years, GDI engines have gained significant market penetration in the automobile industry owing to better fuel economy and drivability. In this study, an accelerated ash loading method was tested by doping lubricating oil into the fuel for a GDI engine. Emission tests were performed at different ash loads with different driving cycles and GPF combinations. The results showed that the GPF could significantly reduce particle emissions to meet the China 6 regulation. With further ash loading, the filtration efficiency increased above 99% and the effects on fuel consumption and backpressure were found to be limited, even with an ash loading of up to 50 g/l.

The issue of car-to-pedestrian impact safety has received more and more attention. For leg protection, a legform impactor with 2 degrees-of-freedom (DOF) proposed by EEVC is required in current regulations for injury assessment, and the Japan Automobile Manufacturers Association Inc. (JAMA) and Japan Automobile Research Institute (JARI) have developed a more biofidelic pedestrian legform since 2000. However, studies show that those existing legforms may not be able to cover some car-to-pedestrian impact situations. This paper documents the development of a new pedestrian legform with 4 DOFs at the knee-joint. It can better represent the kinematics characteristics of human knee-joint, especially under loading conditions in omni-direction impacts. The design challenge is to solve the packaging problem, including design of the knee-joint mechanisms and layout of all the sensors in a limited space of the legform.

Urea-based selective catalytic reduction (SCR) of nitric oxides (NOx) is a key technology for heavy-duty diesel engines to achieve the increasingly stringent NOx emission standards. The aqueous urea injection control is critical for urea-SCR systems in order to achieve high NOx conversion efficiency while restricting the tailpipe ammonia (NH3) slip. For Euro VI emission regulation, an advanced control strategy is essential for SCR systems since its NOx emission limits are tighter and test procedure are more stringent compared to Euro IV and Euro V. The complex chemical kinetics of the SCR process has motivated model-based control design approaches. However, the model is too complex to allow real-time implementation. Therefore, it is very important to have a reduced order model for SCR control system.

Urea selective catalytic reduction (SCR) is a key technology for heavy-duty diesel engines to meet the increasingly stringent nitric oxides (NOx) emission limits of regulations. The urea water solution injection control is critical for urea SCR systems to achieve high NOx conversion efficiency while keeping the ammonia (NH3) slip at a required level. In general, an open loop control strategy is sufficient for SCR systems to satisfy Euro IV and Euro V NOx emission limits. However, for Euro VI emission regulation, advanced control strategy is essential for SCR systems due to its more tightened NOx emission limit and more severe test procedure compared to Euro IV and Euro V. This work proposed an approach to achieve model based closed loop control for SCR systems to meet the Euro VI NOx emission limits. A chemical kinetic model of the SCR catalyst was established and validated to estimate the ammonia storage in the SCR catalyst.

According to the statistics of National Highway Traffic Safety Administration, driver’s cognitive distraction, which is usually caused by drivers using mobile phones, has become one of the main causes of traffic accidents. To solve this problem and guarantee the safety of man-vehicle-road system, the most critical work is to improve the accuracy of driver’s cognitive state detection. In this paper, a novel driver’s cognitive state detecting method based on LightGBM (Light Gradient Boosting Machine) is proposed. Firstly, cognitive distraction experiments of making calls are carried out on a driving simulator to collect vehicle states, eye tracking and EEG (electron encephalogram) data simultaneously and feature extraction is conducted. Then a classifier considering road and individual characteristics used for detecting cognitive states is trained based on LightGBM algorithm, with 3 predefined cognitive states including concentration, ordinary distraction and extreme distraction.

Lane-changing systems have been developed and applied to improve environmental adaptability of advanced driver assistant system (ADAS) and driver comfort. Lane-changing control consists of three steps: decision making, trajectory planning and trajectory tracking. Current methods are not perfect due to weaknesses such as high computation cost, low robustness to uncertainties, etc. In this paper, a novel lane changing control method is proposed, where lane-changing behavior is analogized to parallel parking behavior. In the perspective of host vehicle with lane-changing intention, the space between vehicles in the target adjacent lane can be regarded as dynamic parking space. A decision making and path planning algorithm of parallel parking is adapted to deal with lane change condition. The adopted algorithm based on rules checks lane-changing feasibility and generates desired path in the moving reference system at the same speed of vehicles in target lane.

Metal foil is a widely used material in the automobile industry, which not only is the honeycomb barrier material but is also used as current collectors in Li-ion batteries. Plenty of studies proved that the mechanical property of the metal foil is quite different from that of the metal sheet because of the size effect on microscopic scale, as the metal foil shows a larger fracture stress and a lower ductility than the metal sheet. Meanwhile, the fracture behavior and accurate constitutive model of the metal foil with the consideration of the strain rate effect are widely concerned in further studies of battery safety and the honeycomb. This article conducted experiments on 8011H18 aluminum foil, aiming to explore the quasi-static and dynamic tension testing method and the anisotropic mechanical behavior of the very thin foil. Two metal foil dog-bone specimens and three types of notched specimens were tested with a strain rate ranging from 2 × 10−4/s to 40/s and various stress states.

Highway traffic safety has been the most serious problem in current society, statistics show that about 70% to 90% of accidents are caused by driver operational errors. The autonomous emergency braking (AEB) is one of important vehicle intelligent safety technologies to avoid or mitigate collision. The AEB system applies the vehicle brakes when a collision is eminent in spite of any reaction by the driver. In some technologies, the system forewarns the driver with an acoustic signal when a collision is still avoidable, but subsequently applies the brakes automatically if the driver fails to respond. This paper presents the development and implementation of a rear-end collision avoidance system based on hierarchical control framework which consists of threat assessment layer, wheel slip ratio control layer and integrated-electro-hydraulic brake (IEHB) actuator control layer.

Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.

Studying traffic accidents by using naturalistic driving data has become increasingly appealing for its potential benefits in improving road safety. This paper presents findings from a field test which has been conducted on 50 taxis in the urban areas of Beijing for 10 months using Video Drive Recorders (VDRs). The VDR used in this study could record the information of vehicle front view video, vehicle states, as well as driver operations immediately before and after an event. The drivers were given no specific instructions during the test, and the instrumentation for data collection was unobtrusive. Important safety-relevant parameters, such as vehicle speed, pre-event maneuver, time headway, time-to-collision, and driver reaction time, were calculated with precision. Based on these parameters, an analysis into features and causes of rear-end conflicts is performed.