Power control strategy for preventing thermal failure of passively cooled automotive battery packs

Safety mechanism is required for an automotive battery pack to prevent thermal failure which could lead to catastrophic events. Passively cooled battery packs can prevent thermal failure by conducting adaptive control of battery power without any external cooling device. The key to this power control is how to secure battery safety while minimizing energy loss. This paper proposes a novel, adaptive power control strategy for automotive passive-cooling battery packs. Four different cases with electrochemical battery model are simulated and compared to each other according to a city driving profile. Driving simulation result confirmed that the present power control algorithm is an effective solution for preventing thermal failure along with improving energy efficiency of automotive battery packs.     

Performance evaluations of LED headlamps

Due to rapid progress in LED (Light Emitting Diode) technology, LEDs have become increasingly prevalent in applications to automotive lighting. This paper studies recent trends of LED headlamps along with various experiments regarding photometric characteristics, glare, and visibility. Experimental results are compared to those of halogen and HID (high intensity discharge) headlamps. LED headlamps are found to be still inferior to conventional headlamps with respect to glare. However, many properties of LED headlamps (luminous intensity, beam width, energy efficiency, and design) are competitive with halogen and HID headlamps. The findings in this investigation will henceforth be reported to the Korean Motor Vehicle Safety Standard (KMVSS).     

Identifying factors influencing the slow market diffusion of electric vehicles in Korea

Transportation - Electric vehicles (EVs) are considered as a driving force behind the automotive industry’s transformation based on eco-friendliness and high energy efficiency. Unlike...     

Field tests for evaluating cooperative intersection signal violation warning system (CISVWS)

This paper demonstrates the results of field tests for assessing a cooperative intersection signal violation warning system (CISVWS), which consists of (a) hardware, including an in-vehicle warning device, roadside antenna, and traffic signal controller, and (b) software to operate and test the cooperative system through vehicle to infrastructure (V2I) communication systems. Field tests were performed under real traffic situations in order to test the system in terms of the initiation time of the signal violation warning from the signal controller, the activation and duration of on board equipment (OBE), and the warning delay based on the relationships between distance variables, including the safe stopping distance, and the location of road side equipment (RSE). Findings from the field test at the real-world signalized intersection sites indicated that the system would be capable of reducing red light violations and intersection collisions through use of the in-vehicle warning device at signalized intersections.     

Development of a biology inspired manufacturing system for machining transmission cases

Disruptions in automated manufacturing systems for machining automotive parts caused by system changes and disturbances reduce the productivity, and increase the downtime as well as the cost of products. To cope with these challenges, the paper presents a biology inspired manufacturing system (Bio-MS). The model of Bio-MS is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee’s foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To realize the Bio-MS, the cognitive agent and swarm intelligence were proposed. The disturbances happening when machining the transmission cases at an automotive company in Korea were analyzed to classify them and to find out the corresponding management methods. Currently, the system utilization was too low due to the manual recovery, only 70–76 percent of total production time is used for manufacturing and the rest of the time is wasted in different disturbances. The Bio-MS with autonomous behaviors adapts efficiently to the changes of the manufacturing environment. It enables to increase the system utilization more than 80 percent.     

Robust design optimization of suspension system considering steering pull reduction

This paper presents robust design optimization method to reduce steering pull phenomenon. One of the biggest causes of steering pull phenomenon is tolerance of suspension system such as hard point, spring, damper and bush. Therefore, the relationship between suspension systems and steering pull phenomenon has as nonlinear characteristics. But, it can be very difficult to evaluate the analytical design sensitivity. Thus, it is impossible to directly apply a well-developed optimization algorithm based on gradient information. To avoid these difficulty, this study uses sequential approximation optimization process based on a meta-model. The robust design process has 28 random design variables with tolerance. For efficient design process, the sample variances for the design goals are approximated from meta-models. The proposed approach required only 62 evaluations until it converged. Optimal design reduced the drift by 80% and its deviation by 38.7%, respectively. This result proves that the suggested design method of suspension system is effective and useful.     

Objective evaluation of door-closing sound quality based on physiological acoustics

This paper presents a new method to objectively quantify the sound quality of doors closing in premium passenger cars. In previous works, psychoacoustic parameters have been used for objective quantification. However, these parameters do not agree well with subsequent subjective assessments. Therefore, the correlation between the psychoacoustic parameters and the subjective rating of door closing sounds in sampled cars is low, and it is not sufficient to use psychoacoustic parameters as an objective metric to quantify the quality of door-closing sounds. In this paper, a new method is proposed to objectively quantify the sound quality based on physiological acoustics and statistical signal processing. A gammatone filter is used as a pre-processing method in models of the auditory system and kurtosis, which is the fourth-order moment of the temporal signal and is used to extract quantitative information about the quality of door-closing sounds. The new metric obtained from the proposed method is highly correlated to subjective ratings and has been successfully applied to the quantification of door-closing sound quality.     

Enhancement of aerodynamic performance through high pressure relief in the engine room for passenger car using cfd technique

High pressure acting on the vehicle’s body plays an important role in deciding the aerodynamic drag. An idea has been suggested to enhance the aerodynamic performance for small passenger car by relieving the high pressure in the engine room. The high pressure inside the engine room can be released to the outside of the vehicle through a hole perforated on the wheel house liner. About 1 % of the drag coefficient can be improved with the 1.88 % of the radiator air mass flow rate increment by installing the top hole with slots on the wheel house liner. Flow simulations are performed at the driving velocity of 110 km/h with the moving wall condition of the same velocity. The tire is rotating to catch more precise flow physics around a tire and wheelhouse liner.     

A New Method for Accurately Estimating the Weight of Moving Vehicles Using Piezoelectric Sensors and Adaptive-footprint Tire Model

Summary This paper presents new methods for estimating the axle weight of a moving vehicle, using two piezoelectric sensors and adaptive-footprint tire model. It is more difficult to weigh vehicles in motion accurately than to weigh standing vehicles. The difficulties in weighing moving vehicles result from sensor limitations as well as dynamic loading effects induced by vehicle/pavement interactions. For example, two identical vehicles with the same weight will generate sensor signals that differ in the shape and the peak value, depending the tire pressure, vehicle speed, road roughness, and sensor characteristics. This paper develops a method that is much less sensitive to these variable factors in determining the axle weight of a moving vehicle. In the developed method, first the piezoelectric sensor signal is reconstructed using the inverse dynamics of a high-pass filter representing the piezoelectric sensor. Then, the reconstructed signal, is normalized, using the nominal road/tire contact length obtained using an adaptive-footprint tire model, and then integrated. Experiments are performed with 3 vehicles of known weight ranging from 1,400 kg to 28,040 kg. The developed method is compared to two other algorithms. Results show that the developed method is most consistent and accurate.