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In order to investigate the soot formation process in a diesel spray flame, simultaneous imaging of soot precursor and soot particles in a transient spray flame achieved in a rapid compression machine was conducted by laser-induced fluorescence (LIF) and by laser-induced incandescence (LII) techniques. The 3rd harmonic (355nm) and the fundamental (1064nm) laser pulses from an Nd:YAG laser, between which a delay of 44ns was imposed by 13.3m of optical path difference, were used to excite LIF from soot precursor and LII from soot particles in the spray flame. The LIF and the LII were separately imaged by two image-intensified CCD cameras with identical detection wavelength of 400nm and bandwidth of 80nm. The LIF from soot precursor was mainly located in the central region of the spray flame between 40 and 55mm (270 to 370 times nozzle orifice diameter d0) from the nozzle orifice. The LII from soot particles was observed to surround the soot precursor LIF region and to extend downstream.

This paper introduces the characteristics of the 4 wheel independent driving/4 wheel independent steering (4WID/4WIS) electric vehicle (EV). Models of Subsystems and the vehicle are constructed based on Matlab/simulink. The vehicle model allows the inputs of different drive torques and steer angles of four wheels. The dynamic characteristics of drive motors and steer motors are considered, and also it can reflect the vehicle longitudinal dynamics change due to the increase of the mass and inertia of the four wheels. Besides, drive mode selection function that is unique to this type vehicle is involved. Simulations and analyses of crab, oblique driving and zero radius turning which are the special conditions of 4WID/4WIS EV are conducted. The results show that the model can reflect the dynamic response characteristics. The model can be used to the simulation analyses of handling, stability, energy saving and control strategies verification of 4WID/4WIS EVs.

A direct numerical simulation of turbulent premixed flames in a constant volume vessel is conducted to understand flame-wall interactions and heat loss characteristics under the pressure rising condition. The contribution of the burnt region to the total heat flux is more significant compared to the reaction region. The velocity profiles indicate inward and outward motions. The profile of the turbulent kinetic energy is damped by the wall, and no distinct turbulence production is observed. Since the turbulence is weakened in the burnt region, the effect of near wall turbulence to the total wall heat flux is considered to be limited.

This paper proposed a collision avoidance strategy that take over the control of ego vehicle when faced with urgent collision risk. To improve the applicability of collision avoidance strategy in complex scenarios, the theory of ICS (Inevitable Collision State) is introduced to evaluate the collision risk and compute the trigger flag of the system, and vehicle dynamic is taken into account when modeling ego vehicle to predict ego vehicle’s following moving. Vehicle specific characteristics including reaction time of the braking system and the braking force increasing process are taken into account. In order to reduce injury caused by collision accidents and minimize disruption to drivers, slight steering is added on top of emergency braking. The direction of the steering angle is determined according to IM (Imitating Maneuvers) The flow chart of the strategy is presented in the paper.

Inerters have become a hot topic in recent years, especially in vehicle, train, and building suspension systems. The performance of a passive inerter and a semi-active inerter was analyzed and compared with each other and it showed that the semi-active inerter has much better performance than the passive inerter, especially with the Hybrid control method. Eight different layouts of suspensions were analyzed with a quarter car model in this paper. The adaptation of dimensionless parameters was considered for a semi-active suspension and the semi-active inerters. The performance of the semi-active inerter suspensions with different layouts was compared with a semi-active suspension with a conventional parallel spring-damper arrangement. It shows a semi-active suspension, with more simple configuration and lower cost, has similar or better compromise between ride and handling than a semi-active inerter with the Hybrid control.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

Due to the high cost of torque sensors, a calculation model of transient torque is required for real-time coordinating control purpose, especially in hybrid electric powertrains. This paper presents a feedforward calculation method based on mean value model of turbocharged non-EGR diesel engines. A fitting variable called fuel coefficient is defined in an affine relation between brake torque and fuel mass. The fitting of fuel coefficient is simplified to depend only on three variables (engine speed, boost pressure, injected fuel mass). And a two-layer feedforward neural network is utilized to fit the experimental data. The model is validated by load response test and ETC (European Transient Cycle) transient test. The RMSE (root mean square error) of the brake torque is less than 3%.

Electromagnetic Valve Actuation (EVA) is considered to be a potential substitute of conventional valvetrains for automotive engines. However, valve quiet-seating (soft-landing) is difficult to be achieved. The EVA system and hence its’ mathematic model is nonlinear. Therefore, when linear control is used for EVA, firstly, the model has to be linearized at an equilibrium point through Taylor expansion. Consequently, the linearized model and control are valid only for a small range around the equilibrium point. This paper presents a control strategy for the whole transition of EVA, which combines exact linearization with Linear Quadratic Regulator (LQR). Firstly, the nonlinear EVA model is transformed to be linear in a new coordinate by using exact linearization, so the nonlinear model is not involved. Then the exact-linearized model is used for the EVA control with LQR.

To adhere to stringent environmental regulations, SI (spark ignition) engines are required to achieve higher thermal efficiency. In recent years, EGR (exhaust gas recirculation) systems and lean-burn operation has been recognized as key technologies. Under such operating conditions, reducing CCV (cycle-to-cycle variation) in combustion is critical to the enhancement of overall engine performance. Flow-field CCV is one of the considerable factors affecting combustion in engines. Conventionally, in research on flow fields in SI engines, the ensemble average is used to separate the measured velocity field into a mean component and a fluctuation component, the latter of which contains a CCV component and a turbulent component. To extract the CCV of the flow field, previous studies employed spatial filter, temporal filter, and POD (proper orthogonal decomposition) methods.

Three-dimensional direct numerical simulations of methane-air turbulent premixed flame propagating in homogenous isotropic turbulence are conducted to investigate local and global flame structure in thin reaction zones. GRI-Mech 3.0 is used to represent methane-air reactions. The equivalence ratio of unburned mixture is 0.6 and 1.0. For a better understanding of the local flame structure in thin reaction zones, distributions of mass fractions of major species, heat release rate and temperature are investigated. To clarify effects of turbulence on the local and global flame structures, the statistical characteristics of flame elements are also revealed.

Wet multiple plate clutches consist of friction plates, on which a friction material is bonded, and mating plates that are plain metal plates. Since the frequency and the range of load in the field of forklift trucks vary widely and are more severe than those for passenger cars, the wet multiple plate clutches on forklift trucks are often damaged. Damaged clutches that were returned from the field typically had 3 types of symptoms: 1.Only the friction material was damaged, 2.Only the mating plates were deformed, 3.Both symptoms were observed. It was clear that the cause of these symptoms depended on the difference of the operating application and the strength criteria of each part. This showed that a design guide for wet multiple plate clutches considering the strength balance between the two parts according to the work application was required. The relevant flow chart of this design process was proposed.

A new dynamic tire model for estimating the longitudinal/lateral road-tire friction force was derived in this paper. The model was based on the previous Dugoff tire model, in consideration of its drawback that it does not reflect the actual change trend that the tire friction force decreases with the increment of wheel slip ratio when it enters into the nonlinear region. The Dugoff model was modified by fitting a series of tire force data and compared with the commonly used Magic Formula model. This new dynamic friction model is able to capture accurately the transient behavior of the friction force observed during pure longitudinal wheel slip, lateral sideslip and combined slip situation. Simulation has been done under different situations, while the results validate the accuracy of the new tire friction model in predicting tire/road friction force during transient vehicle motion.

Research of Adaptive Cruise Control (ACC) is an important issue of intelligent vehicle (IV). As we all known, a real and experienced driver can control vehicle's speed very well under every traffic environment of ACC working. So a direct and feasible way for establishing ACC controller is to build a human-like longitudinal control algorithm with the simulation of driver behavior of speed control. In this paper, a novel fuzzy self-tuning control algorithm of ACC is established and this controller's parameters can be tuned on-line based on the evaluation indexes that can describe how the driver consider the quality of dynamical characteristic of vehicle longitudinal dynamics. With the advantage of the controller's parameter on-line self-tuning, the computational workload from matching design of ACC controller is also efficiently reduced.

The accuracy of tire forces directly affects the vehicle dynamics model precision and determines the ability of the model to develop the simulation platform or design the control strategy. In the high slip angle, due to the complex interactions at tire-road interfaces, the forces generated by the tires are high nonlinearity and uncertainty, which pose issues in calculating tire force accurately. This paper presents a hybrid physical and data-driven tire force calculation framework, which can satisfy the high nonlinearity and uncertainty condition, improve the model accuracy and effectively leverage prior knowledge of physical laws. The parameter identification for the physical tire model and the data-based compensation for the unknown errors between the physical tire model and actual tire force data are contained in this framework. First, the parameters in the selected combined-slip Burckhardt tire model are identified by the nonlinear least square method with tire test data.

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.

A lightweight design method of vehicle dash insulators is proposed and investigated in this paper. The lightweight dash insulator, which is composed of double layers of cotton felt with different density and a layer of polyethylene (PE) film and has 55% decrease in weight, is developed and applied in a passenger car, instead of the traditional “heavy layer-soft layer” dash insulator. To evaluate the NVH performance of the lightweight dash insulator, the noise reduction (NR) level index is calculated by using SEA simulation and the sound pressure level and sound qualities in the vehicle are tested under the driving conditions for wide open throttle acceleration in third gear and 60km/h cruising in fourth gear. The simulation and test results show that the vehicle with the lightweight dash insulator has better NVH performance.

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.

Taking a good longitudinal braking performance on flat and level road of tractor and semi-trailer combination as a target, in order to achieve an ideal braking force distribution among axles, while the vehicle deceleration is just depend on the driver's intention, not affected by the variation of semi-trailer mass, the paper proposes a model based vehicle mass identification and braking force distribution strategy. The strategy identifies the driver's braking intention via braking pedal, estimates semi-trailer's mass during the building process of braking pressure in brake chamber, distributes braking force among axles by using the estimated mass. And a double closed-loop regulation of the vehicle deceleration and utilization adhesion coefficient of each axle is presented, in order to eliminate the bad effect of mass estimation error, and enhance the robustness of the whole algorithm. A simulation is conducted by utilizing MATLAB/Simulink and TruckSim.

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.

Transport vehicles consume a large amount of fuel with low efficiency, which is significantly affected by drivers' behaviors. An assessment system of eco-driving pattern for buses could identify the deficiencies of driver operation as well as assist transportation enterprises in driver management. This paper proposes an assessment method regarding drivers' economic efficiency, considering driving conditions. To this end, assessment indexes are extracted from driving economy theories and ranked according to their effect on fuel consumption, derived from a database of 135 buses using multiple regression. A layered structure of assessment indexes is developed with application of AHP, and the weight of each index is estimated. The driving pattern score could be calculated with these weights.