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Published by AUTO FAN Magazine Co. Ltd.

Table of Content

    25 January 2020, Volume 42 Issue 1 Previous Issue    Next Issue
    Research on Local Path Planning Algorithm for Unmanned Vehicles
    Peng Xiaoyan, Xie Hao, Huang Jing
    2020, 42 (1):  1-10.  doi: 10.19562/j.chinasae.qcgc.2020.01.001
    Abstract ( 1744 )   PDF (2245KB) ( 1869 )   Save
    The local path planning algorithm of unmanned vehicle has certain requirements for the safety and real-time performance of obstacle avoidance, and the smoothness of obstacle avoidance path. In this paper, a local path planning algorithm based on discrete optimization is proposed, which uses cost function to evaluate the safety and smoothness of discretely generated candidate paths, and then obtains the local optimal path through the weighted calculation of each cost function. Aiming at the randomness of obstacles movement, a moving obstacles safety cost function is designed based on motion estimation combined with Gaussian convolution. Considering the curvature and its continuity of path, a path smoothness cost function is designed. A new coordinate transformation calculation method is adopted to convert the path from the s-ρ coordinate system to the earth Cartesian coordinate system, enhancing real-time performance. Finally, a PreScan / Matlab co-simulation and a real vehicle experiment on “Yuan Fei” unmanned vehicle experimental platform are both carried out. The results show that the path planning algorithm proposed not only enables the unmanned vehicle to safely and reasonably avoid the static and moving obstacles, but also fully meets the real-time requirements of local path planning algorithm
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    Lateral Adaptive Backstepping Switching Control for Robot-driven Vehicles
    Su Shuhua, Chen Gang
    2020, 42 (1):  11-19.  doi: 10.19562/j.chinasae.qcgc.2020.01.002
    Abstract ( 426 )   PDF (1403KB) ( 389 )   Save
    In order to achieve the stable steering and path tracking of vehicle at different speeds, a lateral adaptive backstepping switching control scheme for robot-driven vehicle is proposed. A 7-DOF vehicle longitudinal and lateral dynamics model is set up, and based on the concept of equivalent moment of inertia, a dynamics model for the steering manipulator of driving robot is also established. The virtual control variables, fuzzy membership function and Lyapunov function of each subsystem in steering manipulator are defined and fuzzy adaptive inversion controller and state switcher are designed. Comparative simulations on the scheme proposed and other control schemes and human-driven vehicle test verify the effectiveness of the scheme proposed
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    Active Rescue System of Unmanned Vehicle Platoon in Fog Weather
    Bian Chentong, Yin Guodong, Xu Liwei, Zhang Ning, Zhu Tong
    2020, 42 (1):  20-26.  doi: 10.19562/j.chinasae.qcgc.2020.01.003
    Abstract ( 368 )   PDF (1113KB) ( 497 )   Save
    For reducing the traffic accidents caused by the overspeed of manned vehicles on road in fog weather, an active rescue system is designed for unmanned vehicle platoon. When the system detects the overspeed of an manned vehicle with obstacles in front of it, the platoon can controlled to form a barrier by lane-change and changing formation to force the manned vehicle to reduce speed before collision and avoid accident. To verify the effectiveness of the proposed active rescue system, two simulations are conducted for comparison. The results of simulation show that the proposed system can effectively reduce the collision accidents of manned vehicles in fog weather
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    Research on Identity Authentication in V2X CommunicationsBased on Elliptic Curve Encryption Algorithm
    Zhang Jiayan, Li Fei, Li Ruxiang, Li Yalin, Song Jiaqi, Zhou Qiyang
    2020, 42 (1):  27-32.  doi: 10.19562/j.chinasae.qcgc.2020.01.004
    Abstract ( 343 )   PDF (905KB) ( 523 )   Save
    With the development of automotive information technology, the internet of vehicles (IOV) between vehicles and vehicle-cloud interconnected communication has become a reality. However, while the IOV brings convenience to people, it also gives hackers the opportunity to conduct the unauthorized capture or revision of the data packets sent by using fake identity, thus posing a security threat to the user. Therefore, the identity authentication of both parties in vehicle communications plays a vital role in vehicle safety. In this paper, on the basis of comparison on commonly used public key encryption algorithms, it is proposed to use elliptic curve cryptography and other security strategies to verify the authenticity of the connected vehicle network users. The results of experiments show that the adoption of the method proposed to perform the encryption and authentication of inter-vehicle communications effectively ensure the communications security of IOV, with 83% less time consumed compared with traditional public key encryption algorithms
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    Research on Virtualization Technology for ComputingPlatform of Intelligent Connected Vehicles
    Yan Gang, Xiao Kun, Chu Wenbo
    2020, 42 (1):  33-37.  doi: 10.19562/j.chinasae.qcgc.2020.01.005
    Abstract ( 508 )   PDF (863KB) ( 595 )   Save
    As the brain of intelligent connected vehicles, the computing platform mostly adopts multi-heterogeneous hardware architecture and uses multiple operating systems to run the environment perception, path planning and vehicle control algorithms with different levels of functional safety and cybersecurity. A virtualized software architecture, adapting to a variety of hardware platforms and multiple application scenarios is proposed in this paper. This architecture enables the resource sharing and partitioning isolation between virtual machines, and provides a variety of fault tolerance and protection mechanisms to concurrently meet the requirements of functional security and cybersecurity. In addition, an efficient communication mechanism between virtual machines and a virtualized performance optimization mechanism are also proposed and verified, which can meet the requirements of computing platform of intelligent connected vehicles
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    Research on Target Recognition and Tracking Based on 3D Laser Point Cloud
    Xu Guoyan, Niu Huan, Guo Chenyang, Su Hongjie
    2020, 42 (1):  38-46.  doi: 10.19562/j.chinasae.qcgc.2020.01.006
    Abstract ( 641 )   PDF (2123KB) ( 1130 )   Save
    Aiming at the obstacle detection problem in environmental perception of unmanned vehicle, a target recognition and tracking method based on onboard lidar is designed. For reducing computation efforts and increasing processing speed, point-cloud filtering and segmentation algorithms are introduced to reduce original laser-point-cloud data, effectively enhancing the real-time performance of detection. Based on SVM classifier, multi-feature compound criteria are used to improve Adaboost algorithm, and three-dimensional point-cloud data are directly processed, retaining perceptual information to the maximum extent and enhancing recognition accuracy. A data correlation method based on maximum entropy fuzzy clustering and corresponding particle filter are proposed to effectively enhance the stability and accuracy of target tracking in complex traffic flow. The data set simulation on Baidu Apollo platform, the experimental verification on self-developed unmanned driving platform and real vehicle verification in small target overlapping and occluding conditions show that the method proposed has good robustness and real-time performance
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    Parking Space Detection Based on BackgroundIllumination Removal and Connected Regions
    Huang Chen, Liu Ze, Luo Yugong, Wang Yongsheng
    2020, 42 (1):  47-51.  doi: 10.19562/j.chinasae.qcgc.2020.01.007
    Abstract ( 280 )   PDF (2146KB) ( 473 )   Save
    The vision-based automatic parking system is susceptible to uneven illumination, and when image information is complicated, it is often difficult to make an accurate judgment on parking spaces. In view of this, a parking space detection method is proposed based on background illumination removal and connected regions. Fish-eye cameras are used to capture the images of the surroundings around the vehicle, a panoramic bird's eye view is obtained by processing the captured images, which is then input into parking space recognition system. The removal of background illumination from initial image effectively solves the problem of uneven illumination and complex background. A parking space extraction method based on connected regions is designed, which simplifies the extraction of parking spaces and reduce the computation efforts in parking space recognition. The results of experiment show that the methods proposed can achieve the effective recognition and accurate location of parking spaces
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    K-means++ Clustering and Recognition of Driver'sCollision Avoidance Steering Behavior
    Zhao Zhiguo, Feng Jianxiang, Zhou Liangjie, Wang Kai, Hu Haorui, Zhang Haishan, Ning Zhonglin
    2020, 42 (1):  52-58.  doi: 10.19562/j.chinasae.qcgc.2020.01.008
    Abstract ( 529 )   PDF (1639KB) ( 525 )   Save
    A clustering algorithm based on driver's collision avoidance steering behavior's characteristics is proposed according to driver's steering behavior data under different working conditions in this paper. Firstly a driving simulator is built, on which the driving behavior data are collected under the conditions of fixed radius steering, conventional lane change and emergency collision avoidance steering. The features of emergency collision avoidance steering are qualitatively analyzed by comparing the steering behavior data of normal driving with that in emergency collision avoidance conditions. Then the Pearson correlation coefficient method is used to analyze the correlation between the measurement variables of driver's steering behavior and emergency collision avoidance steering behavior, with a result showing that the steering condition is most correlated to the rotational speed of steering wheel. After that, with the rotational speed of steering wheel as the clustering characteristic parameter, clustering is conducted on steering behavior data by using K-means++ algorithm, and the steering behaviors are divided into normal steering (including fixed-radius steering and lane change steering) and emergency collision avoidance steering, achieving the recognition of emergency collision avoidance steering. Finally real vehicle verification test is performed and the results indicate that the K-means++ clustering algorithm proposed can effectively identify the steering behavior of driver for emergency collision avoidance with a clustering accuracy up to 96.7%
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    Calibrated Calorimetry for Measuring the Specific Heat Capacityand Heat Generation Rate of Lithium-ion Battery
    Wu Qingyu, Zhang Hengyun, Li Junwei
    2020, 42 (1):  59-65.  doi: 10.19562/j.chinasae.qcgc.2020.01.009
    Abstract ( 876 )   PDF (1447KB) ( 936 )   Save
    The measurement of the specific heat capacity and heat generation rate of lithium ion battery by using calibrated calorimetry is studied in this paper, in which the specific heat capacity of lithium ion battery is determined and its heat generation rate in high rate discharge is measured based on temperature change and heat loss calibration of battery. The results of experiment show that the specific heat capacity of lithium ion battery increases with the rise of ambient temperature, exhibiting a linear positive correlation. The heat generation of battery in discharge process has time varying and transient features and the average heat generation rate of battery is positively correlated with the square of discharge rate. In addition, the heat generation experiment with constant power demonstrates that using calibrated calorimetry to measure the specific heat capacity and heat generation rate of battery is accurate, simple and nondestructive
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    Experimental Study on Safety of Automotive NCMBattery Under Different Abuse Conditions
    Chen Jiqing, Liu Mengmeng, Zhou Yunjiao, Lan Fengchong, Luo Jihuan
    2020, 42 (1):  66-73.  doi: 10.19562/j.chinasae.qcgc.2020.01.010
    Abstract ( 551 )   PDF (2320KB) ( 645 )   Save
    In order to improve the use safety of electric vehicle and reveal the mechanism and behavior features of NCM battery runaway in extreme conditions, thermal runaway experiments on an automotive 12 A·h NCM lithium battery under three abuse conditions including over-temperature, overcharge and internal short-circuit are conducted to explore the changes of key parameters such as the voltage and temperature of battery in the course of thermal runaway and comparatively analyze the features of three thermal runaway behaviors. The results show that there is an obvious evolution process of NCM battery thermal runaway, and abnormal changes of battery voltage, which sharply rises suddenly and then sharply fall rapidly, can be taken as the condition to judge the occurrence of thermal runaway caused by overcharge. There is a certain reaction time between the occurrence of overcharge thermal runaway and severely burn out of battery, and under the same conditions, the extents of severity and destruction of overcharge runaway are larger than that of thermal runaway caused by internal short-circuit and over-temperature. In the end, suggestions are given based on experiment results for improving the safety of NCM battery under thermal, electric and mechanical abuse conditions
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    A Study on Parameter Matching of Hydro-mechanicalTransmission System Based on Genetic Algorithm
    Zhu Zhen, Cai Yingfeng, Chen Long, Xia Changgao, Shi Dehua
    2020, 42 (1):  74-80.  doi: 10.19562/j.chinasae.qcgc.2020.01.011
    Abstract ( 398 )   PDF (1067KB) ( 386 )   Save
    In this paper, analyses on the kinematics, kinetics and energy management of a hydro-mechanical compound transmission are carried out with its assembly schemes and basic parameters determined. Multi-objective genetic algorithm based on Pareto optimal principle is used to study the matching issue of transmission system, including the selection of optimization objectives and the determination of design variables and constraints and so on. Multi-objective optimization model of transmission system is established based on modeFRONTIER, climbing slope and specific fuel consumption are chosen as objective functions for power performance and fuel economy respectively, and Multi-objective genetic algorithm is adopted combined with the design of experiment, to conduct global search on the model for seeking the optimum solution. The results show that the arithmetic mean of climbing slope is 27.26°, with a 95% confidence interval of [26.36°,28.16°] and a Pareto optimal solution of 27.93°; the arithmetic mean of specific fuel consumption is 208.88 g/(kW·h), with a 95% confidence interval of [208.62,209.13]/g/(kW·h) and a Pareto optimal solution of 206.76 g/(kW·h). As the iterative steps of optimization increase, both objectives, i.e. climbing slope and specific fuel consumption will convergence in a small range, and the Pareto optimal solution of design variables well meet the matching requirements of transmission system
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    Research on the Modeling of Axial Flux In-wheel MotorBased on Magnetic Field Reconstruction Method
    Li Tao, Zhang Youtong, Liang Yuxiu, Yang Ye, Ai Qiang
    2020, 42 (1):  81-87.  doi: 10.19562/j.chinasae.qcgc.2020.01.012
    Abstract ( 369 )   PDF (3164KB) ( 538 )   Save
    The axial flux of the in-wheel motor has the advantages of high power density, high efficiency and short axial length. However, its special 3D structure makes it difficult to concurrently achieve both rapidity and accuracy in electromagnetic design by analytical method or finite element method. In order to reduce the computation efforts while improving the accuracy of results, taking the detailed design of a yokeless axial flux in-wheel motor with amorphous alloy stator tooth as an example, the calculation model of its air-gap flux density is given by combining 3D magnetic field reconstruction method with Maxwell stress tensor method. The calculation formulas for the axial electromagnetic force of lateral rotor and electromagnetic torque are derived, and the waveform of stator magnetic linkage and back electromotive force are analyzed. The results of 3D field reconstruction method are verified by 3-D transient finite element analysis. The results show that 3D field reconstruction method has good accuracy with less calculation time
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    Electrical Parameters Influence Characteristics and VibrationIsolation Performance of Self-powered MR Damper
    Gao Xiang, Niu Junchuan, Liu Zhihui, Tian Lili
    2020, 42 (1):  88-93.  doi: 10.19562/j.chinasae.qcgc.2020.01.013
    Abstract ( 360 )   PDF (1116KB) ( 361 )   Save
    In order to investigate the influence of electrical parameters on self-powered MR damper, the circuit model of self-powered MR damper with rectifier is established firstly. The frequency response function is deduced. Reducing resistance and inductance of the generator can improve electrical efficiency of self-powered MR damper significantly. Subsequently a quarter vehicle suspension system with self-powered MR damper based on Bingham model is introduced and the mechanical-electrical coupling equation is deduced. The vibration isolation capability is investigated in time and frequency domain respectively. The transmissibility is investigated with electrical parameters altering. The results show that compared with the passive suspension system sprung mass velocity and acceleration is declined by 51% and 78%, the amplitude of transmissibility is reduced about 5 dB, respectively. Enhancing resistance can weaken the vibration isolation capability. Transmissibility is mitigated due to the increment of capacitance and inductance, especially in higher frequency range
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    Experimental Study on Initial Jet Breakup and InfluencingFactors Near Nozzle Area in Diesel Engine
    Gao Yongqiang, Zhong Bing, Tao Lili, Liu Yonghui, Wang Xibo, Chang Jing
    2020, 42 (1):  94-99.  doi: 10.19562/j.chinasae.qcgc.2020.01.014
    Abstract ( 361 )   PDF (3542KB) ( 292 )   Save
    A visual test platform for the fuel injection atomization process is designed and built. With a nanosecond level flash lamp as the exposure light source, the digital camera and the long-distance micro imaging technology with high magnification and high resolution are used to visually capture the microstructure of the initial disturbance of the jet surface near the fuel nozzle area. Combined with the image post-processing technology, the jet surface structure parameters and injection parameters are measured and analyzed quantitatively. The study shows that the generation, deformation and breakup of the initial jet surface wave, liquid wire and liquid drop near the nozzle are closely related to the injection pressure, cavitation and environmental backpressure. With the increase of the injection pressure, the initial jet disturbance increases, and the “potholes” and “bulges” structures on the jet surface are more close to the nozzle. Cavitation promotes the formation of the initial jet disturbance, liquid wire and liquid drop, resulting in increase of the spray cone angle. With the increase of the environmental back pressure, the shear effect between the jet and the environmental medium increases and the initial breakup of the jet can be effectively promoted, and the liquid wire around the jet can be further broken to form droplet, which effectively improves the atomization quality
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    Study on Road Roughness Identification Based on Four Typical Neural Networks
    Li Jie, Guo Wencui, Zhao Qi, Gu Shengfeng
    2020, 42 (1):  100-107.  doi: 10.19562/j.chinasae.qcgc.2020.01.015
    Abstract ( 356 )   PDF (1444KB) ( 613 )   Save
    To identify road roughness, four typical neural networks and their application selection, input scheme optimization and evaluation indicators are studied, and a solution scheme is proposed for the input selection and input combination optimization of four typical neural networks. A four DOF plane model for vehicle system vibration is built, with the input and output of neural networks obtained by simulation. 32 input schemes of each neural network are determined by orthogonal experimental design, the evaluation indicators for the input scheme of each neural network under common road grade B and 60 km/h driving speed are obtained, and the optimal input scheme of each neural network and the optimal neural network among four typical ones are selected through variance analysis. The results show that among four typical neural networks, NARX neural network is the optimal one in identifying road roughness with its correlation coefficient and root mean square error of optimal input scheme being 96.75% and 0.003 3 respectively
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    Research on Engine Life Prediction Method Based on Characteristics Evaluation
    Gu Guangyu, Liu Jianmin, Qiao Xinyong, Jiang Hongyuan, Yang Hao
    2020, 42 (1):  108-113.  doi: 10.19562/j.chinasae.qcgc.2020.01.016
    Abstract ( 449 )   PDF (827KB) ( 629 )   Save
    For the problem of the large quantity of characteristics needed in the process of engine performance evaluation and prediction, and the non-uniform standard of optimal selection and evaluation of characteristic parameters, this paper presents an optimal selection method of engine state characteristic parameters based on multi-index comprehensive evaluation. A certain engine is taken as the research object, and 12 original characteristics parameters of this engine are analyzed to establish a series of evaluation indicators from the aspects of correlation, monotonicity, discreteness, etc. to realize object evaluation of the state characteristics. The entropy weight is proposed to determine the weight of multiple indexes objectively in the perspective of information content. And the optimal ranking of the state characteristic parameters is realized through ideal points and similarity. By weighted fusion of the selected feature parameters by similarity index, the progress fuzzy rule model is established and the engine life prediction is realized
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    Study on the Internal Flow and Heat Transferin the Air-to-Air Intercooler of a SUV
    Qiu Sawei, Wang Zhenhu, Liao Bin, Xia Erli, Li Luoxing
    2020, 42 (1):  114-120.  doi: 10.19562/j.chinasae.qcgc.2020.01.017
    Abstract ( 457 )   PDF (2703KB) ( 650 )   Save
    A study on the internal flow and heat transfer in an air-to-air intercooler of a SUV is conducted by using 3D dual-stream model, the velocity field, temperature field and pressure field in the internal cold and heat flows of the intercooler under different driving conditions are analyzed, and the existence of eddy in internal flow field and the distribution of local high and low temperature and pressure areas are effectively predicted. The comparison results of the temperatures obtained by 1D, 3D, 1D/3D simulations and test verification show that among three simulation schemes, the 1D/3D co-simulation has highest accuracy, the results of 3D and 1D/3D simulations on temperature distribution are relatively close, and the relative error between 3D simulation and test is within 5%. The study verifies the feasibility of simulation with the dual-stream model for intercooler, providing references for enhancing engine intake efficiency and the research on the internal heat-transfer of intercooler
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    Research on Aeroacoustic Optimization of Vehicle Rearview Mirror
    Jiang Hao, Lai Wanhu, Zhang Siwen, Dong Guoxu, Jia Wenyu, Pang Jian
    2020, 42 (1):  121-126.  doi: 10.19562/j.chinasae.qcgc.2020.01.018
    Abstract ( 432 )   PDF (2223KB) ( 661 )   Save
    Aiming at the aeroacoustic problem of the exterior rearview mirror of a car, a fast optimization scheme for aerodynamic noise is proposed based on the calculation of exterior flow field around vehicle, with the results of optimization verified by corresponding tests. In unsteady numerical simulation, the aerodynamic noises on the surface of front side window are analyzed by detached eddy simulation combined with computational aeroacoustics. The results indicate that after optimization, the intensity of aerodynamic noise source on the surface of front side window is obviously weakened in most frequency bands, and the sound pressure level at different monitoring points is lowered, meanwhile the results of real vehicle road test show that the scheme of aeroacoustic optimization based on exterior flow field simulation is feasible and reasonable. Both these demonstrate that exterior flow field simulation can provide effective guidance for in-vehicle aeroacoustic optimization in early styling stage, reducing cost and leadtime of vehicle development
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    Research on the Method of Determining Road Condition Cycles ofDurability Test of Correlated User Automobile Test Field
    Zhao Lihui, Li Jiaxin, Jing Qing, Liu Bin, Zheng Songlin
    2020, 42 (1):  127-133.  doi: 10.19562/j.chinasae.qcgc.2020.01.019
    Abstract ( 489 )   PDF (1600KB) ( 487 )   Save
    A multi-objective optimization method based on genetic algorithm is proposed to solve the problem that it is difficult to determine the road condition cycle times of vehicle durability test in the current correlated user test field. Based on the collected user road load data, the damage target of different parts in the whole life cycle of the vehicle is extrapolated. Combined with the basic damage matrix of each road condition on the test field, the “test field-user” equivalent damage correlation model is established. The traditional least square method and genetic algorithm are adopted to solve the damage equivalent model, and an optimal criteria is proposed for multiple non-inferior solutions of the genetic algorithm. The effectiveness of the two algorithms is analyzed by comparing the damage on test field and user target. The results show that cycles of each road condition based on generic algorithm is more reasonably, and the damage level of different parts is better reproduced, while the damage on test field according to the least square method is generally small and only a few parts can reproduce the user damage. The research can provide reference and basis for more reasonable establishment of test field durability test specifications and effective evaluation of vehicle reliability and durability
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    Research on Quantitative Evaluation of Automotive ProductPerformances Based on FAHP-FQFD Method
    Yu Ning, Jiang Jing, Chen Jiajia
    2020, 42 (1):  134-139.  doi: 10.19562/j.chinasae.qcgc.2020.01.020
    Abstract ( 259 )   PDF (1189KB) ( 395 )   Save
    For better conducting quantitative evaluation on the performances of automotive products, fuzzy analytic hierarchy process (FAHP) is introduced into fuzzy quality function deployment (FQFD), and a novel quantitative evaluation method for automotive products performance is created. Firstly, FAHP is used to calculate the requirement weights of different automotive products performances based on experts' evaluation. Then weight probability method is applied to revise weighting factors with comprehensive consideration of customers' evaluation. Finally, on the basis of setting up multi-stage fuzzy quality function house model, the performance indicators of automotive products are calculated. The implementation process of this approach is verified by an example of automotive engine hood. The results show that the FAHP-FQFD evaluation method created can effectively fulfill the quantitative evaluation on automotive product performances with their outcome better reflecting actual situation, providing intuitive scientific basis for the selection of vehicle design schemes
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