Objective evaluation of human perception of automotive sound based on physiological signal of human brain

This paper presents a novel approach to apply the physiological signal of the human brain to the sound quality evaluation of automotive sound. In the previous work, psychoacoustic metrics were applied to the sound quality evaluation of automotive sound. Loudness among psychoacoustic metrics is used for one of major sound metrics for the objective evaluation of the sound quality of the acceleration sound inside a car. Subjective evaluation of the sound quality of the acceleration sound shows different results depending on the two different groups of participants. One group liked powerful sound when a car is accelerated: the other group liked the refine sound. Loudness of the acceleration sound is not correlated with the subjective rating of the former group whilst it is correlated with that of the latter group. This evaluation suggests that for the people who like the powerful acceleration sound, it needs to find the sound metric for the objective evaluation of the sound quality of the acceleration sound. In this paper, a driver’s brain signal is measured using electroencephalography (EEG) when a driver hears the acceleration sound of passenger cars. The signal is analyzed to obtain the relationship between brain signals and human perception. According to these results, the alpha wave correlates to the human perception of powerful sound quality of passenger cars. This interesting relationship can be used for objective evaluation of passenger car sounds.     

Fault-tolerant yaw moment control with steer — and brake-by-wire devices

This paper presents an fault-tolerant yaw moment control for a vehicle with steer-by-wire (SBW) and brake-by-wire (BBW) devices. SBWs and BBWs can give active front steering (AFS) and electronic stability control (ESC) functions, respectively. Due to motor-driven devices, actuator and sensor faults are inherent in SBW and BBW, and can cause a critical damage to a vehicle. Simple direct yaw moment control is adopted to design a vehicle stability controller. To cope with actuator failure, weighted pseudo-inverse based control allocation (WPCA) with variable weights is proposed in yaw moment distribution procedure. Simulations on vehicle simulation software, CarSim®, show the proposed method is effective for fail safety.     

Effect of fuel metering on combustion and emissions of a PFI gasoline engine during fast startup under an HEV-like mode

In this paper, the transient conditions during fast startup are investigated to develop a fuel metering strategy under HEV-like mode. The fuel mixture preparation and its effects on the combustion are analyzed in detail. Specifically, the combustion in the first cycle is characterized under both conventional low-speed cranking startup and HEV-like fast startup modes. The test results show that the enhancement of cranking speed has marginal effects on mixture preparation in the first cycle. However, it prolongs the combustion duration and reduces HC emissions. The sensitivity of the fuel metering is evaluated for the initial cycles. The combustion in the 3rd ~ 5th cycles during startup is found to be fairly sensitive to the fuel metering due to the effects of transient fuel film vaporization. The fuel metering in the first cycle has the most significant effect on the combustion and emissions during fast startup. Optimized fuel metering in the first cycle shows effective reduction of HC emissions during fast startup process.     

Fatigue assessment of rear axle under service loading histories considering the strengthening and damaging effects of loads below fatigue limit

Accurately predicting the fatigue life is the basis for the reliability and lightweight design of automobile parts. However, the predicted lives under service loadings on the basis of the S-N curve from constant amplitude loads from existing methods often seems conservative compared with real lives, because of ignoring the strengthening effect of loads below fatigue limit. In this paper, a fatigue damage model, which is modification of Miner’s Rule, was established for the fatigue assessment under service loadings by means of taking into account the strengthening and damaging effects of loads below fatigue limit. Then this model and conventional Miner’s Rule are applied to the estimate the fatigue life of a torsion beam rear axle using the loading history recorded on proving ground. Finally, verification tests are performed on MTS road load simulator test bed. Results of predicted lives and fatigue tests demonstrate that the accuracy of the predicted life could be greatly improved by taking into account the strengthening and damaging effect of loads below fatigue limit.     

Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.     

Effect of steady airflow field on drag and downforce

The purpose of this study is to examine the effect of the steady airflow field of a rear spoiler on the coefficients of drag (C_D) and downforce (C_DF). The type of spoiler is suggested as a two-jointed arm model that mimics the flapping flight mechanism of the Canada goose. Computational fluid dynamics (CFD) technique was used for the steady airflow analysis of a vehicle implemented with various spoiler topologies. We evaluated C_D and C_DF due to the three types of airfoils and the five phases of each airfoil. We obtained the following conclusions from the results: (1) We found that the best cases for C_D and C_DF were the case of Phase 5 and symmetry airfoil, and the case of Phase 1 and reverse airfoil, respectively. (2) It is clear that C_D becomes the largest at Phase 1 of the reverse airfoil, since the eddy magnitude at the rear of the vehicle is the largest, and C_DF also becomes the largest during that phase, since the pressure distribution on the upper surface of the spoiler is very large. (3) As Phase 1 moves to Phase 5 in the same type of airfoil, it is advantageous for C_D and disadvantageous for C_DF, respectively.     

Impact phase in frontal vehicle-pedestrian collisions

The paper presents an alternative model developed in order to determine the pedestrian throw distance, taking into account ten distinct parameters. The collision dynamics, after the primary and secondary impact (pedestrian’s head hitting the vehicle windshield-hood area) between the vehicle and the pedestrian, entails the pedestrian ‘carrying’ phase onto the vehicle hood-windshield. Other parameters influencing the pedestrian throw distance, such as road inclination, friction coefficient between the pedestrian and the ground, vehicle and pedestrian mass, pedestrian launch angle are considered for the analysis. A comparison between the results obtained through the formula proposed in this paper and the results obtained by other researchers as well as a comparison with the results extracted from the casuistry analyzed by the authors on both accident reconstruction and laboratory tests is carried out.     

Robust estimation of maximum tire-road friction coefficient considering road surface irregularity

An accurate estimation of the maximum tire-road friction coefficient may provide higher performance in a vehicle active safety control system. Unfortunately, real-time tire-road friction coefficient estimation is costly and necessitates additional sensors that must be installed and maintained at all times. This paper proposes an advanced longitudinal tire-road friction coefficient estimation method that is capable of considering irregular road surfaces. The proposed algorithm uses a stiffness based estimation method, however, unlike previous studies, improvements were made by suggesting a third order model to solve problems related to nonlinear mu-slip curve. To attain the tire-road friction coefficient, real-time normalized force is obtained from the force estimator as exerted from the tire in the low slip region using the recursive least squares method. The decisive aspect of using the suggested algorithm lies in its low cost and versatility. It can be used under irregular road conditions due to its capability of easily obtaining wheel speed and acceleration values from production cars. The newly improved algorithm has been verified to computer simulations as well as compact size cars on dry asphalt conditions.     

Estimation of vehicle sideslip angle and tire-road friction coefficient based on magnetometer with GPS

This paper presents a method that estimates the vehicle sideslip angle and a tire-road friction coefficient by combining measurements of a magnetometer, a global positioning system (GPS), and an inertial measurement unit (IMU). The estimation algorithm is based on a cascade structure consisting of a sensor fusing framework based on Kalman filters. Several signal conditioning techniques are used to mitigate issues related to different signal characteristics, such as latency and disturbances. The estimated sideslip angle information and a brush tire model are fused in a Kalman filter framework to estimate the tire-road friction coefficient. The performance and practical feasibility of the proposed approach were evaluated through several tests.