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The active sound generation systems (ASGS) for electric vehicles (EVs) play an important role in improving sound perception and transmission in the car, and can meet the needs of different user groups for driving and riding experiences. The active sound synthesis algorithm is the core part of ASGS. This paper uses an efficient variable-range fast linear interpolation method to design a frequency-shifted and pitch-modified sound synthesis algorithm. By obtaining the operating parameters of EVs, such as vehicle speed, motor speed, pedal opening, etc., the original sound signal is interpolated to varying degrees to change the frequency of the sound signal, and then the amplitude of the sound signal is determined according to different driving states. This simulates an effect similar to the sound of a traditional car engine. Then, a dynamic superposition strategy is proposed based on the Hann window function.

During the drivability test process, a large amount of noise generated by a series of internal and external factors of the vehicle reduces the accuracy of the drivability evaluation. To solve this problem, this paper introduces the EEMD denoising method and compares the denoising effects of the EMD denoising method and EEMD denoising method on the original signal using the entropy weight evaluation index. In addition, the optimal parameter setting is obtained by comparing the denoising results of different parameter settings in the EEMD denoising method. The results show that when the white noise is integrated 3000 times and the standard deviation of white noise is 0.1, the EEMD noise reduction method is the best, and the comprehensive score of noise reduction is 0.732 points higher than that of EMD.

The technology of active sound generation (ASG) for automobiles is one of the most effective methods to flexibly achieve the sound design that meets the expectations of different user groups, and the active sound synthesis algorithms are crucial for the implementation of ASG. In this paper, the Kaiser window function-based the harmonic synthesis algorithm of automobile sound is proposed to achieve the extraction of the order sounds of target automobile. And, the suitable fitting functions are utilized to construct the mathematical model between the engine speed information and the amplitude of the different order sound. Then, a random phase correction algorithm is proposed to ensure the coherence of the synthesized sounds. Finally, the analysis of simulation results verifies that the established method of the extraction and synthesis of order sound can meet the requirements of target sound quality.

The multi-functional mechanical arm equipped on engineering vehicle can achieve different functions by installing different mechanism devices through the interface at the end of the mechanical arm. It can achieve functions like engineering construction and road rescue. Mechanical arm systems often work in complex environments, which requires good reliability and safety of the boom system. When the mechanical boom is working, the pressure of each luffing cylinder is large, and the contact force and acceleration of each boom are complex, which requires a certain degree of verification and optimization before it can be put into production. In this paper, a virtual prototype of a vehicle mounted hydraulic mechanical arm with four booms is established. Through ADAMS, the dynamic analysis of mechanical arm under multiple working conditions is carried out, the movement parameter changes and the pressure changes of each luffing cylinder are analyzed.

In the process of truck overload and over-limit detection, it is necessary to detect the characteristics of the vehicle's size, type, and wheel number. In addition, in some vehicle vision-based load recognition systems, the vehicle load can be calculated by detecting the vibration frequency of specific parts of the vehicle or the change in the length of the suspension during the vehicle's forward process. Therefore, it is essential to quickly and accurately identify vehicle features through the camera. This paper proposes a vehicle feature recognition method based on image semantic segmentation and Python, which can identify the length, height, number of wheels and vibration frequency at specific parts of the vehicle based on the vehicle driving video captured by the roadside camera.

This paper addresses the brake pad particle emission during the braking process of a vehicle in motion. The frictional-constant contact between the disc brake and pads results in an increased temperature and wear of the pads. The emission of brake pad particles into the atmosphere leads to an increase in air pollution and hence becomes hazardous to the human body. In this paper, a wheel brake disc is installed in a ventilation system where the specific air flow is introduced in order to investigate the thermal performance and the emission of particles from the brake pads. A mathematical model using the fundamental parameters of the brake disc and ventilation system is established. The behavior of the heat transfer is studied using computational fluid dynamics (CFD). The particle emission rate from the pads is calculated under the assumption of uniform constant pressure distribution at the contact surface of the brake disc and pad.

When dump trucks unload dusty materials, dust particles with a diameter of 1 to 75 microns slide out of the dump body and float into the air. Dust particles naturally settle down spending a few hours, which causes air pollution. People who work in this environment daily suffer serious physical harm. To study the movement of dust particles during the unloading process, a scaled-down model is used to simulate the process of dump truck unloading gravel, and a high frame rate camera is used to record the movement trajectory of dust particles during the unloading process. In this paper, by observing the movement process of unloading dust particles by dump trucks, based on the principle of dynamics, a mathematical model describing the unloading of dust particles in the dump body and a mathematical model of the diffusion of dust particles in the air are established. Take the small gravel sampled at the construction site as an example of the experiment.

The plug-in hybrid electric vehicle (PHEV) gradually moves into the mainstream market with its excellent power and energy consumption control, and has become the research target of many researchers. The energy management strategy of plug-in hybrid vehicles is more complicated than conventional gasoline vehicles. Therefore, there are still many problems to be solved in terms of power source distribution and energy saving and emission reduction. This research proposes a new solution and realizes it through simulation optimization, which improves the energy consumption and emission problems of PHEV to a certain extent. First, on the basis that MATLAB software has completed the modeling of the key components of the vehicle, the fuzzy controller of the vehicle is established considering the principle of the joint control of the engine and the electric motor.

Based on the technology of the order tracking and extraction, a software for the modulation of sound quality of automotive order sound is developed in this paper. The order analysis, the amplitude modulation of order sound in specific speed range and the calculation of the functional expression of the order sound amplitude are integrated in this software. Furthermore, a side-valve interpolation correction algorithm (SV-ICA) is proposed to solve the problem that the smooth transition of the order sound curve at endpoints cannot be guaranteed, which would result in the appearance of abnormal noise in the modulated sounds. The application of built software in constructing the automobile sounds with the sound quality of sportiness is demonstrated.

In order to study the influence of low-viscosity oil on automobile pollutant emissions reduction, three different 0W20 oil samples were prepared with oil 5W30 as the base oil. Parameters such as the oil viscosity, ash, and element content were tested at different stages, speeds, and accelerations of the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The results showed the effects of low-viscosity oil on exhaust emissions reduction were mainly concentrated in the low-speed and extra high-speed segment. At the low-speed segment, especially in the starting stage, carbon monoxide (CO), total hydrocarbon (THC), and non-methane hydrocarbon (NMHC) emissions can be reduced. The use of low ash oil can reduce nitrogen oxides (NOx) emissions; the methane (CH4) emissions can be reduced by increasing the Zinc (Zn) content in engine oil moderately.

The lightweight design of a vehicle can save manufacturing costs and reduce greenhouse gas emissions. For the off-road vehicle and truck, the chassis frame is the most important load-bearing assembly of the separate frame construction vehicle. The frame is one of the most assemblies with great potential to be lightweight optimized. However, most of the vehicle components are mounted on the frame, such as the engine, transmission, suspension, steering system, radiator, and vehicle body. Therefore, boundaries and constraints should be taken into consideration during the optimal process. The finite element (FE) model is widely used to simulate and assess the frame performance. The performance of the frame is determined by the design parameters. As one of the largest components of the vehicle, it has a lot of parameters. To improve the optimum efficiency, sensitivity analysis is used to narrow the range of the variables.

The non-contact overload recognition method refers to the method of detecting the vibration state of the vehicle through visual recognition without touching the vehicle, and then calculating the vehicle load in combination with the vehicle dynamics model to determine whether the passing vehicle is overloaded. Due to the convenience of detection, low cost of infrastructure and informatization, this method has great advantages in the field of overload identification. However, the model used in this recognition method is the single mass vibration model at present, which will have a large error due to the interaction between the front and rear suspension, and the position of the center of mass needs to be acquired in the recognition process, which is difficult in the actual identification process. In this paper, a vehicle vibration model containing two modes of vibration is proposed, and uses Sobol algorithm to analyze the parameter sensitivity of the model.

To study the mechanism of the effect of low-viscosity oils on engine friction loss reduction so as to improve the vehicle fuel economy of the Worldwide harmonized Light vehicles Test Cycle (WLTC) by upgrading the Society of Automotive Engineers (SAE) viscosity grade of the factory fill oil from 5W30 to 0W20, eight 0W20 oil samples were blended with different doses of base oil, viscosity modifier (VM), and friction modifier (FM). Theoretical analysis by AVL-EXCITE simulation of the key friction pairs combined with practical engine friction torque test and vehicle WLTC fuel consumption tests were carried out. The results showed that 0W20 oils can effectively reduce the engine friction torque by 5.64 Nm and the friction loss by 11.95% with the throttle fully opened; while with the throttle closed, the friction torque decreased by 3.53 Nm and the friction loss by 11.26%, resulting to the improvement of the vehicle WLTC fuel economy by 2.08%.

The aerodynamic noise of the reactive muffler is generated inside the muffler and mixed with the noise of the muffler body, which is difficult to be measured in the exhaust system. Based on two-microphone transfer function method and transmission loss of mufflers in the absence of airflow, this paper proposes a method for measuring the aerodynamic noise of the muffler. On the built-in muffler aerodynamic noise test bench, a special sampling tube was designed to measure the aerodynamic noise of the muffler at different flow velocity. For the sound absorption end with large reflection coefficient, the test and simulation data have large error at low frequency, and a correction formula that can eliminate the reflection of sound waves at the end of the test pipeline and form multiple reflections in the upstream and downstream is derived.

The ride performance and stability of the vehicle will decrease while the vehicle passing a deceleration bump with relatively high speed. If the speed is too low, the road efficiency and ride comfort will be affected. It is essential to identify the proper speed taking into account all the factors. In this paper, the dynamic model of the vehicle passing through the deceleration bump is established. Three kinds of indicators vibration weighted acceleration RMS, maximum vertical vibration acceleration and wheel load impact coefficient, are used to comprehensively evaluate the ride comfort and safety. The highway model, vehicle model, and common trapezoidal cross-sections bump models are set up in Carsim. Parameters such as vertical acceleration and tire force at different vehicle speeds are obtained. Then use the spline interpolation method to fit the data, and comprehensively consider the three indicators to get the best speed.

In summer, the relatively low temperature water condenses in the evaporator when the vehicle air-conditioning (AC) is running. At present, the vehicle AC condensate water without well utilization is directly wasted. The condenser’s thermal transfer performance has a great influence on the AC performance, and to increase the convective heat transfer coefficient (CHTC) is the key to its design. In this paper, a method of using atomized condensate water (CW) to enhance the condenser’s thermal transfer performance is proposed, which can make the most of the CW's cold energy. It achieves the reuse of CW and increases the condenser’s CHTC. First, the CW flow calculation model in the evaporator and the calculation model of the condenser enhanced thermal transfer using atomized CW are both set up. The influence of the evaporation degree of atomized CW particles in the air on the enhancement effect is comprehensively considered.

Signage recognition is one of the hot topics in recent years. It has important applications in intelligent traffic and autonomous driving of smart cars. This paper designs a road marking recognition method combining OPSA point set distance and wavelet transform. The method consists of three main phases: 1) image denoising, restoration, 2) feature extraction, and 3) image recognition. First, a Gaussian-smoothing filter used to attenuate or remove irrelevant information in the image, enhance related information in the image, and achieve image denoising. In the feature extraction stage, the feature extraction and recognition method based on wavelet transform adopted to overcome the deficiency of the traditional Fourier feature extraction method, ensure that high frequency information is not lost, and low frequency information is not lost. Finally, the OSPA point set used to identify distance markers.

Energy has the worldwide concern since the World War. Recently, the energy harvesting technology has got more attraction in different fields and applications. Hence, in a world where energy becomes rare and expensive, even the small quantities are worth to be harvested where it can be exploited in different applications. Vehicle suspension is one of the vibration power dissipation sources in which the undesired vibration is dissipated into heat waste. Accordingly, the principal motivation of this study is exploitation the conflict between the potentially harvested power and vehicle dynamics in automotive suspension system induced by road irregularity. Therefore, in terms of RMS conflict diagrams, the conflict between the potential power and vehicle dynamics are sufficiently and comprehensively defined considering a vehicle speed of 20 m/s.

The automobile exhaust energy can be recovered by the thermoelectric module generator(TEG). Owing to the complex urban traffic, the exhaust gas’s temperature fluctuations are resulted, which means the unstable hot-end temperature of the TEG. By installing solid heat capacity material(SHCM) to the area between the outer wall of the exhaust pipe and the TEG, it is possible to appropriately reduce the temperature fluctuation, but there is still a fluctuation of the TEG’s power output. Then by adding voltage filter circuit (VFC) after the TEG, the power output stability can be improved. This research uses SHCM and VFC to improve the stability of the exhaust gas generation. Firstly, the three-dimensional heat transfer model of the exhaust pipe thermoelectric power generation system is established. The heat capacity materials with low thermal resistance and high heat capacity were selected as the research object based on previous research.

It’s not easy to start the engine in winter, especially in frigid highlands, because the low temperature increases the fuel’s viscosity, decreasing the lubricating oil flow ability and the storage performance of battery. Current electrical heating method can improve the engine starting performance in low temperature condition, but this method adds an external power to the engine, leading to the engine cannot maintain an efficient energy utilization. A warming device using the solar energy is designed to conserve the energy during the daytime, and directly warm up the engine at the time when the engine turns off for a long time, especially during the night. A solar collector installed on the top of the vehicle is used to convert the solar energy to the thermal energy, which is then transferred to the heat accumulator that contain the phase-change medium which can increase the heat storage performance.