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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.

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.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

Tracked vehicles are widely used for agriculture, construction and many other areas. Due to high emissions, hybrid electric driveline has been applied to tracked vehicles. The hybrid powertrain design for the tracked vehicle has been researched for years. Different from wheeled vehicles, the tracked vehicle not only requires high mobility while straight driving, but also pursues strong steering performance. The paper takes the hybrid track-type dozers (TTDs) as an example and proposes an optimal design of a novel power-split powertrain for TTDs. The commercial hybrid TTD usually adopts the series hybrid powertrain, and sometimes with an extra steering mechanism, which has led to low efficiency and made the structure more complicated. The proposed three-planetary-gear power-split hybrid powertrain can overcome the problems above by utilizing the characteristics of planetary gear sets.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

The RON(Research Octane Number) is the most important indicator of motor petrol, and the petrol refining process is one of the important links in petrol production. However, RON is often lost during petrol refining and RON Loss means the value of RON lost during petrol refining. The prediction of the RON loss of petrol during the refining process is helpful to the improvement of petrol refining process and the processing of petrol. The traditional RON prediction method relied on physical and chemical properties, and did not fully consider the high nonlinearity and strong coupling relationship of the petrol refining process. There is a lack of data-driven RON loss models. This paper studies the construction of the RON loss model in the petrol refining process.

Velocity prediction on hilly road can be applied to the energy-saving predictive control of intelligent vehicles. However, the existing methods do not deeply analyze the difference and diversity of road slope driving characteristics, which affects prediction performance of some prediction method. To further improve the prediction performance on road slope, and different road slope driving features are fully exploited and integrated with the common prediction method. A rolling prediction-based multi-scale fusion prediction considering road slope transition driving characteristics is proposed in this study. Amounts of driving data in hilly sections were collected by the advanced technology and equipment. The Markov chain model was used to construct the velocity and acceleration joint state transition characteristics under each road slope transition pair, which expresses the obvious driving difference characteristics when the road slope changes.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

In order to improve the drivability and reduce the clutch friction loss, low-cost slope sensor is used in hill-start control of AMT vehicles. After the power spectrum analysis of the original signal and the design of the digital filter, the angle of the slope is obtained with short enough delay and small enough noise. By using this slope angle information, slope resistance force can be calculated online so that the vehicle can be prevented from sliding backward and optimal launch control can be realized. The digital filter of slope angle signal and the optimal controller of dry clutch engagement are embedded in the TCU (Transmission Control Unit) of a micro-car Geely Panda. Real-vehicle experiments are carried out with optimal clutch controller, which shows that the hill-start with low-cost slope sensor and optimal clutch controller can provide successful vehicle launch with little driveline shock. In addition, it can also avoid backward sliding and engine over-speed effectively.

With the development of cellular communication technology and for the sake of reducing drag resistance, the multi-lane platoon technology will be more prosperous in the future. In this article, the cooperative vehicle platoon method on the public road is represented. The method’s architecture is mainly composed of the following parts: decision-making, path planning and control command generation. The decision-making uses the finite state machine to make decision and judgment on the cooperative lane change of vehicles, and starts to execute the lane change step when the lane change requirements are met. In terms of path planning, with the goal of ensuring comfort, the continuity of the vehicle state and no collision between vehicles, a fifth-order polynomial is used to fit every vehicle trajectory. In terms of control command generation module, a model predictive control algorithm is used to solve the multi-vehicle centralized optimization control problem.

To improve traditional heavy commercial vehicles performance, this paper introduces a novel hydraulic hub-motor auxiliary system, which could achieve auxiliary driving and auxiliary braking function. Firstly, the system configuration and operation modes are described. In order to achieve coordinating control and distribution of the engine power between mechanical and hydraulic paths, the paper proposes an optimal algorithm based on enhance of vehicle slip efficiency and the results show that displacement of hydraulic variable pump relates with the transmission gear ratio. And then the hydraulic pump displacement controller is designed, in which the feedforward and feedback strategy is adopted. Considering the characteristics of hydraulic hub-motor auxiliary system, a layered auxiliary drive control strategy is proposed in the paper, which includes signal layers, core control layers and executive layers.

Recent research has shown that butanol, instead of ethanol, has the potential of introducing a more suitable blend in diesel engines. This is because butanol has properties similar to current transportation fuels in comparison to ethanol. However, the main downside is the high cost of the butanol production process. Acetone-butanol-ethanol (ABE) is an intermediate product of the fermentation process of butanol production. By eliminating the separation and purification processes, using ABE directly in diesel blends has the potential of greatly decreasing the overall cost for fuel production. This could lead to a vast commercial use of ABE-diesel blends on the market. Much research has been done in the past five years concerning spray and combustion processes of both neat ABE and ABE-diesel mixtures. Additionally, different compositions of ABE mixtures had been characterized with a similar experimental approach.

For the purpose of lessening fuel consumption, engine noise, shift jerk and clutch friction work in the shift process of Automatic Mechanical Transmission (AMT), a fuzzy-bang bang dual mode control strategy for engine rotate speed is put forward in this paper, which takes the advantages of time optimal control and fuzzy control. The combined control strategy is applied to the shift process control of AMT test minibus named SC6350 and proved to be successful by the experimental results.

In order to study the influence of body flexibility on the truck ride comfort, a 4 DOF half vibration model of truck based on the motion synthesis between rigid body and body flexibility is established using elastic beam theory of equal section with both free ends. At the same time, a corresponding 2 DOF rigid vibration model is also built. The frequency response functions of system and response variables of two models are derived based on front wheel. The power spectral densities and the root mean square values of body acceleration, dynamic deflections and relative dynamic loads are obtained. By comparing the simulation results of rigid-elastic model and rigid model, it shows that body flexibility has a great impact on truck ride comfort and it cannot be ignored.

Many kinds of drive systems can be adopted by a pure electric vehicle. In order to select the most suitable drive system, the configuration features of different drive systems were analyzed. After matching the drive systems in a pure electric vehicle, the dynamic performance comparison has been carried out; and on the basis of establishing the vehicle energy consumption model and taking the city driving cycle as an example, the economic comparison of these drive systems has been completed.

In order to improve the mode switching performance of parallel hybrid electric vehicles (PHEV) and make better use of the dynamics of the vehicle, this paper proposes a three-stage control method for the start-up mode of start-up, speed synchronization, and clutch slip based on the response characteristics of actual vehicle components and the complex working conditions of the actual road. In the speed synchronization phase, a coordinated control method of “engine speed active following + continuously variable transmission (CVT) speed ratio motor speed limiting” is proposed. The real vehicle test results show that the engine starting-up coordinated control method can significantly accelerate the speed synchronization and shorten the starting-up mode duration during the rapid acceleration, so that the vehicle’s power performance can be well played and the ride comfort can be effectively guaranteed.

In this paper, gear ratios of a two-speed transmission system are optimized for an electric passenger car. Quasi static system models, including the vehicle model, the motor, the battery, the transmission system, and drive cycles are established in MATLAB/Simulink at first. Specifically, since the regenerative braking capability of the motor is affected by the SoC of battery and motors torque limitation in real time, the dynamical variation of the regenerative brake efficiency is considered in this study. To obtain the optimal gear ratios, iterations are carried out through Nelder-Mead algorithm under constraints in MATLAB/Simulink. During the optimization process, the motor efficiency is observed along with the drive cycle, and the gear shift strategy is determined based on the vehicle velocity and acceleration demand. Simulation results show that the electric motor works in a relative high efficiency range during the whole drive cycle.

In recent years, Magneto-rheological (MR) fluid has drawn a lot of attention for its applications in a variety of torque transmission devices, such as brakes, clutches and soft starters of mechanical equipment. Compared with the conventional clutch of vehicle, the novel MR clutch has the advantages of fast response with electronic signal, accuracy control and simple structure without mechanical wear in plates. Besides, MR clutch may be helpful to fast response of vehicle in some situation. Nowadays, most applications of MR fluids in the torque transmission field mainly are used in low-power situation. As far as we know, the proposed effective methods enhancing the output torque of MR devices will increase either the number of fluid gaps or the magnetic field in the MR fluid. This article presents a novel vehicle clutch utilizing magnetorheological fluid and multiple-disc structure.

In this paper, we focus on the active vehicular suspension controller design. A quarter-vehicle suspension system is employed in the system analysis and synthesis. Due to the difficulty and cost in the measuring of all the states, we only choose two variables to construct the feedback loop, that is, the control law is a static-output-feedback (SOF) control. However, the sensor reduction would induce challenges in the controller design. One of the main challenges is the NP-hard problem in the corresponding SOF controller design. In order to deal with this challenge, we propose a two-stage design method in which a state-feedback controller is firstly designed and then the state-feedback controller is used to decouple the nonlinear conditions. To better compensate for the varying vehicle load, a robust load-dependent control strategy is adopted. The proposed design methodology is applied to a suspension control example.

In this paper, it was researched the degradation characteristics of catalytic performance of three kinds of DPFs (C1, C2 and C3, with precious metal concentrations being 15, 25 and 35 g/ft3 respectively) after diesel truck aging. It is found out that the crystallinity of three kinds of DPF samples (Used) in full vehicle aging was higher than that of fresh samples (Fresh) and aged samples (Aged) in the laboratory. Compared with Fresh samples, the concentration of Pt atom in precious metal on the surface of Aged and Used samples tends to decrease in most cases. Activities to CO and C3H8 of Aged and Used samples of three kinds of DPFs had all been degraded, and activity degradation showed a substantial correlation with concentration reduction rate of precious metal on the carrier surface. NO2 productivity of Used samples all rose. Crystallinity of DPF samples after full vehicle aging in Inlet, Middle and Outlet areas successively increased.