Search Results

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.

Fuel cell reactors, as the core components of fuel cell vehicles, have a short life problem that has always limited the development of fuel cell vehicles. The life attenuation curve of fuel cell shows nonlinear characteristics, and there is no model that can accurately predict its effect. This paper is based on the experimental data of the vehicle fuel cell reactor, which is derived from the 600 h durability test run by a 4 kW fuel cell reactor. The relevance vector machine, as a Bayes processing method that supports vector machine, is a data-driven method based on kernel functions. The regression model is established by the relevance vector machine, and the super-parameters are found by genetic algorithm, because the kernel function strongly affects the nonlinearity of the curve, and the decay curve of fuel cell reactor performance is predicted according to four different kernel functions.

In this work, the influences of various real-timely available energy management strategies on vehicle fuel consumption (VFC) and energy flow of a range-extender electric vehicle were studied The strategies include single-point, multi-point, speed-following, and equivalent consumption minimization strategy. In addition, the dynamic programming method which cannot be used in real time, but can provide the optimal solution for a known drive situation was used for comparison. VFCs and energy flow characteristics with different strategies under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) were obtained through computer modeling, and the results were verified experimentally on a range-extender test bench. The experimental results are consistent with the modeled ones in general with a maximum deviation of 4.11%, which verifies the accuracy of the simulation models.

This paper proposes a new evaluation method of analyzing stability and design of a controller for an electric power steering (EPS) system. The main purpose of the EPS system’s control design is to ensure a comfortable driving experience of drivers, which mainly depends on the assist torque map. However, the high level of assist gain and its nonlinearity may cause oscillation, divergence and instability to the steering systems. Therefore, an EPS system needs to have an extra stability controller to eliminate the side effect of assist gain on system stability and attenuate the unpleasant vibration. In this paper, an accurate theoretical model is built and the method for evaluating system quality are suggested. The bench tests and vehicle experiments are carried out to verify the theoretical analysis.

Life prediction is a major focus for a commercial fuel cell stack, especially applied in fuel cell electric vehicles (FCEV). This paper proposes a data driven fuel cell lifetime prediction model using particle swarm optimized back-propagation neural network (PSO-BPNN). For the prediction model PSO-BP, PSO algorithm is used to determine the optimal hyper parameters of BP neural network. In this paper, total voltage of fuel cell stack is employed to represent the health index of fuel cell. Then the proposed prediction model is validated by the aging data from PEMFC stack in FCEV at the actual road condition. The experimental results indicate that PSO-BP model can predict the voltage degradation of PEMFC stack at actual road condition precisely and has a higher prediction accuracy than BP model.

Automobile rubber isolator was subjected to random load cycle for a long time in the service process, and its main rubber material for vibration isolation was prone to fatigue failure. Since the traditional Miner damage theory overlooked the load randomness, it had a prediction error problem. In order to improve the prediction accuracy of rubber fatigue life, the traditional Miner damage theory was modified by random uncertainty theory to predict the rubber fatigue life under random load. Firstly, the rubber dumbbell-shaped test column, which was vulcanized from rubber materials commonly used in vibration isolators, was taken as the research object. The uniaxial fatigue test of rubber under different strain amplitudes and strain mean values was carried out. Then the fatigue characteristic curve of rubber with equivalent strain amplitude as the damage parameter was established.

Gas purge is considered as an essential shutdown process for a PEMFC (Proton Exchange Membrane Fuel Cell), especially in subfreezing temperature. The water flooding phenomenon inside fuel cell flow channel have a marked impact on performance in normal operating condition. In addition, the residual water freezes in the subzero temperature, thus blocking the mass transfer from flow channel to porous media. Therefore, the gas purge course is of primary importance for improvement of performance and durability. The water droplet residing in the flow channel can be purged out due to shearing force of gas. In fact, the flow channel is not completely flat due to surface roughness of gas diffusion layer (GDL), meaning the water droplet may climb over obstacles. Moreover, the water droplet may block the flow channel and then be sheared into films on the surface of GDL.

The durability road test of a vehicle is an important test to verify the reliability of vehicle components. In order to carry out the durability bench test for drive shaft systems of all-terrain vehicles, a method for acquiring time domain signals of articulation angles of the CVJ, input torque, and rotational speeds of drive shaft systems is proposed. The acquired load spectrum of drive shaft systems is preprocessed including deleting small amplitudes, de-drifting, deburring, filtering, etc. Peaks and valleys are extracted from the preprocessed load spectrum. Based on the graphic method and the estimator stabilization method, the upper and lower thresholds of the time domain extrapolation of the load spectrum are determined, and then the peaks and valleys excesses that exceed the upper and lower thresholds are extracted. The generalized pareto distribution function is used to fit the distribution of peaks and valleys excesses.

Because the power unit of electric vehicle has large torque, the rubber mount of electric vehicle is fully compressed under the condition of full throttle acceleration. When designing the mount of electric vehicle, the dynamic-to-static stiffness ratio of mount under the case should be as low as possible to improve the vibration isolation rate of the mount. In this paper, a method for calculating the high frequency dynamic characteristics of rubber isolators under different preloads is presented. Firstly, the dynamic characteristics of rubber specimens under various shear pre-strains were tested. The test results show that the dynamic stiffness of specimen decreases at first and then increases with the increase of shear strain. The viscoelastic parameters of rubber in frequency domain under different pre-strain were identified according to the experimental data. Secondly, a finite element modeling method was proposed.

Tortuosity, viscous characteristic length and thermal characteristic length are three important parameters for estimating the acoustic performance of porous materials, and it is usually measured by ultrasonic measurement technology, which is costly. In this paper, a method for identifying the tortuosity, viscous characteristic length and thermal characteristic length for the porous fiber materials mixed with kapok fiber and two kinds of other fiber materials is proposed. The tortuosity is calculated by using the porosity and high-frequency normal sound absorption coefficient of porous materials. According to the normal sound absorption coefficient curve of porous materials under plane wave incidence, viscous characteristic length and thermal characteristic length are identified through the Johnson-Champoux-Allard-Lafarge (JCAL) model and genetic algorithm by using the measured parameters, the calculated tortuosity and static thermal permeability.

Rubber isolators are widely used under random vibrations. In order to predict their fatigue life, a study on the fatigue analysis methodology for rubber isolators is carried out in this paper. Firstly, taking a mount used for isolating air conditioning compressor vibrations as studying example, accelerations versus time of rubber isolator at both sides are acquired for a car under different running conditions. The acceleration in time domain is transformed to frequency domain using the Fourier transform, and the acceleration power spectral density (PSD) is the obtained. Using the PSD as input, fatigue test is carried for the rubber isolator in different temperature and constant humidity conditions. A finite element model of the rubber isolator using ABAQUS is established for estimating fatigue life, and model validity is verified through static characteristic testing. Dynamic responses of the rubber isolator at frequency domain are calculated if a unit load is applied.

Recently, several datasets have become available for occupant monitoring algorithm development, including real and synthetic datasets. However, real data acquisition is expensive and labeling is complex, while virtual data may not accurately reflect actual human physiology. To address these issues and obtain high-fidelity data for training intelligent driving monitoring systems, we have constructed a hybrid dataset that combines real driving image data with corresponding virtual data generated from 3D driving scenarios. We have also taken into account individual anthropometric measures and driving postures. Our approach not only greatly enriches the dataset by using virtual data to augment the sample size, but it also saves the need for extensive annotation efforts. Besides, we can enhance the authenticity of the virtual data by applying ergonomics techniques based on RAMSIS, which is crucial in dataset construction.

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.

To study the state of health (SOH) of the proton exchange membrane fuel cell (PEMFC), a novel hybrid method combining the advantages of both the model-based and data-driven methods is proposed. Firstly, the model-based method is proposed based on the voltage degradation model to estimate the variation trend, and three parameters reflecting the performance degradation are selected. Secondly, the data-driven (long short-term memory (LSTM)) method is presented to estimate the variation fluctuation. Moreover, the core step of the hybrid method is returning the results of the LSTM method to the power degradation model as the “observation” and modifying related parameters to improve the estimation accuracy. Finally, the sliding window method is applied to solve the problem of the data increase with the increase of the operating time. The results show that the power estimation is better than the current estimation for the SOH estimation.

A new proportional electromagnetic dynamic vibration absorber (EDVA) is proposed for control of engine vibration during idling. The device consists of an electromagnetic actuator attached to the primary structure through elastic element, where the driving force pair is implemented between the reaction-mass and the primary structure. The design of the proportional electromagnetic actuator is realized considering the geometric parameters of the core to achieve nearly constant magnetic force over a broad range of its dynamic displacement but proportional to square of the current. A methodology is proposed to achieve magnetic force proportional to square of current and consistent with the disturbance frequency. The proportional EDVA is subsequently applied to a single-degree-of-freedom primary system with an acceleration feedback control algorithm for attenuation of primary system vibration in a frequency band around the typical idling vibration frequencies.

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.

Cold start capability is one of remaining major challenges in realizing PEMFC (Proton Exchange Membrane Fuel Cell) technology for automotive applications. Gas purge is a common and integral shutdown procedure of a PEMFC automotive in subzero temperature. A dryer membrane electrode assembly (MEA) can store more water before it gets saturated and ice starts to penetrate in the open pores of porous media, thus enhancing cold start capability of a PEMFC. Therefore, gas purge is always performed prior to fuel cell shutdown to minimize residual water in a PEMFC. In the hope of improving effectiveness of purge in a PEMFC vehicle, two important purge parameters are evaluated including purge time and energy requirement. In practice, an optimized gas purge protocol should be developed with minimal parasitic energy, short purge duration and no degradation of components. To conclude, the cold start capability and performance can be consolidated by proper design of gas purge strategies.

Fuel cell vehicles (FCV) have become a promising transportation tool because of their high efficiency, fast response and zero-emission. However, the cold start problem is one of the main obstacles to limit the further commercialization of FCV in cold weather countries. Many efforts have made to improve the cold start ability. This review presents comprehensive heating methods and influence factors of the research progress in solving the Proton Exchange Membrane Fuel Cells (PEMFC) system cold start problems with more than 100 patents, papers and reports, which may do some help for PEMFC system cold start from the point of practical utilization. Firstly, recent achievements and goals will be summarized in the introduction part. Then, regarding the heating strategies for the PEMFC system cold start, different heating solutions are classified into self-heating strategies and auxiliary-heating heating depending on their heating sources providing approach.

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.