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In general, when a problem occurs in a component of powertrains, various phenomena appear, and abnormal noise is one of them. The service mechanics diagnose the noise through analysis by using their ears and equipment. However, depending on their experiences, analysis time and diagnostic accuracy vary greatly. To shorten the analysis time and improve the diagnostic accuracy, we have developed a technology to diagnose powertrain parts that cause abnormal noises. To create the best deep learning model for our diagnosis, we tried to collect many abnormal noises from various parts. The collected noise data was measured under idle and various operating conditions from our vehicles and test cells. This noise data is abnormal noises generated from engines, transmissions, drive system and PE (Power Electric) parts of eco-friendly vehicles. From the collected data, we distinguished good and bad data through detailed analysis in time and frequency domain.

An important trend among vehicle NVH engineers is the production of attractive engine acceleration sound quality for the enhancement of a vehicle's image and performance. In addition, customers have increasing interest and enjoyment in customizing their cars to reflect their personal taste and preferences. The PESS (Personalized Engine Sound System) has been developed for making a unique and individually customizable vehicle concept. The system allows the customers an opportunity to create a variety of engine sounds in a single vehicle using active sound design technology. In this system, three different engine sound concepts are pre-defined, Dynamic, Sporty, and Extreme. Each of the engine sounds can then be adjusted with parameters that determine the timbre, such as main order, rumble, and high order. In addition, the pedal position during acceleration has also been used as a parameter to further personalize the experience.

High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles.

Door slam noise is very important sound, because Door Slam noise gives a big effect in high-class feeling of vehicle and brand identity. But it is very difficult to analyze door slam noise by traditional analysis and overall sound level. Moreover, the short occurrence time of Door Slam noise makes the analysis more difficult. In this paper, we used the latest developed sound quality methods for analyzing Door Slam noise. And we had performed jury test for luxury vehicles. After that we had carried out correlation analysis between objective analysis and subjective test. Finally, we could suggest Door Slam noise Index by linear regression analysis.

In order to understand the automotive PEM fuel cell system, mathematical system modeling is conducted and the model is implemented and simulated by using the Matlab®/Simulink®. The components such as fuel cell stack, air supplier, and radiator are modeled individually and integrated into a system level. The PEM fuel cell system operation control includes thermal management, air supply control, hydrogen supply control, fuel cell stack protection control, and load following control. In the thermal management, the inlet and outlet temperature of coolant are controlled to operate the fuel cell stack in desired temperature range and to prevent flooding inside the fuel cell stack. In air supply control and hydrogen supply control, the flow rates of air and hydrogen are controlled not to starve the fuel cell stack according to the output current. A control structure for the system is developed and confirmed by using the developed simulation model.

When unifying the functions of widely used two-fan, engine cooling system into a single fan unit, the noise and power issues must be addressed. The noise problem due to the increased fan radius is a serious matter especially as the cabin noise becomes quieter for sedans. Of the fan noise components, discrete noise at BPF's (Blade Passing Frequency) seriously degrades cabin sound quality. Unevenly spaced fan is developed to reduce the tones. The fan blades are spaced such that the center of mass is placed exactly on the fan axis to minimize fan vibration. The resulting fan noise is 11 dBA quieter in discrete noise level than the even bladed fan system.

For optimizing the performance of SI engine such as engine torque, fuel consumption, and emissions, various types of system for variable valve timing were developed by many automotive researchers. In this paper, we investigated the relationship between valve timing and intake orifice noise, and suggested how to improve NVH (Noise, Vibration and Harshness) performance as well as engine torque. Some experiments using the engine dynamometer were carried over about 150 different operating conditions. BEM analysis was also conducted in order to calculate acoustic modes of intake system. The results show that the valve timing and overlap of breathing systems have influence on NVH behavior, especially intake orifice noise over whole range of operating conditions. Valve timing and overlap of intake and exhaust valve were optimized in the view of sound quality as well as overall noise level.

Luxury sound is one of the most important sound qualities in a premium passenger car. Previous work has shown that, because of the effects of many different interior sounds, it is difficult to evaluate the luxury sound objectively by using only the A-weighted sound pressure level. In this paper, the characteristics of such sound were first investigated by a systematic approach and a new objective evaluation method for luxury sound-the luxury sound quality index--which was developed by the systematic combination of the seven major interior sound quality indexes based on path analysis. The seven major sounds inside a passenger car were selected by a basic investigation evaluated by the members of a luxury automotive club. Seven major interior sound quality indexes were developed by using sound metrics, which are the psychoacoustic parameters, and the multiple regression method used for the modeling of the correlation between objective and subjective evaluation.

With the advent of cars with computerized engines, drivers sometimes suffer discomfort with “check engine” light problem, and as a result, insist on increasing levels of reliability in their cars. Hence, reliability of the wiring harness has become a very important automotive design characteristic. On one hand, the more secure an engine mounting system is, the more stable the engine wiring harness is. In order to enhance their durability, car manufacturers need to perform many validation tests during the development phase which involves a lot of time and cost. In this study, a newly developed lab-simulation test is proposed to qualify the design of engine mounting and engine wiring early in the design cycle and reduce time and expense. The lab-simulation test has contributed to a significant cost and time reduction and has shown good correlation to the original proving ground test.

This paper presents two closed-loop control methods for monitoring and improving the combustion behavior and the combustion noise on two 4-cylinder diesel engines, in which an in-cylinder pressure and an accelerometer transducer are used to monitor and control them. Combustion processes are developed to satisfy the stricter and stricter regulations on emissions and fuel consumption. These combustion processes are influenced by the factors such as engine durability, driving conditions, environmental influences and fuel properties. Combustion noise could be increased by these factors and is detrimental to interior sound quality. Therefore, it is necessary to develop robust combustion behaviors and combustion noise. For this situation, we have developed two closed-loop control methods. Firstly, a method using in-cylinder pressure data was developed for monitoring and improving the combustion noise of a 1.7L engine. A new index using the values calculated from the data was proposed.

This paper presents a novel method predicting the variation of sound quality of interior noise depending on the change of the proprieties of absorption materials. At the first, the model predicting the interior noise corresponding to the change of the absorption material in engine room is proposed. Secondly the index to estimate the sound quality of the predicted sound is developed. Thirdly the experimental work has been conducted with seven different materials and validated the newly developed index. Finally, this index is applied for the optimization of absorption material to improve the sound quality of interior noise in a passenger car.

The success of improved fuel economy is the proper integration of thermal management components which are appropriately performed to reduce friction and wasted energy. The thermal management systems of vehicle are able to balance the multiple needs such as heating, cooling, or appropriate operation within specified temperature ranges of propulsion systems. Since the propulsion systems of vehicle have changed from a single energy source based on conventional internal combustion engine to hybrid system including more electrical system such as full type of hybrid electric vehicle or plug-in hybrid electric vehicles, a new transition associated with vehicle thermal management arises. More efficient thermal management systems are required to improve the fuel economy in the hybrid electric vehicles because of the driving of electric traction motor and the increase of engine off time. The decrease of engine operation time may not sustain the proper temperature ranges of engine and gearbox.

In this paper, a reconfigurable object-oriented simulator is proposed to analyze the performance of Bluetooth Voice Communication Package (VCP) for telecom purposes like hands-free vehicular communication. It consists of a graphical user interface (GUI) for research or validation engineers to investigate system specific performance. For example, a research engineer can utilize this GUI to analyze a system performance using different noise reduction filtering techniques in vehicular hands-free applications. Also, a validation engineer can utilize this GUI to evaluate vehicular Bluetooth audio quality for different vehicles at different driving conditions (e.g. speeds, fan levels, etc.). The proposed Bluetooth VCP model consists of modules like Audio Equalization (EQ), Acoustic Echo Canceller (AEC), and Noise Suppression (NS). This dynamic GUI platform provides the scope to add and analyze new proposed filtering techniques.

A fractional recirculation of cabin air was proposed and studied to improve cabin air quality by reducing cabin particle concentrations. Vehicle tests were run with differing number of passengers (1, 2, 3, and 4), four fan speed settings and at 20, 40, and 70 mph. A manual control was installed for the recirculation flap door so different ratios of fresh air to recirculated air could be used. Full recirculation is the most efficient setting in terms of thermal management and particle concentration reduction, but this causes elevated CO₂ levels in the cabin. The study demonstrated cabin CO₂ concentrations could be controlled below a target level of 2000 ppm at various driving conditions and fan speeds with more than 85% of recirculation. The proposed fractional air recirculation method is a simple yet innovative way of improving cabin air quality. Some energy saving is also expected, especially with the air conditioning system.

In order to align with net-zero CO2 ambitions, automotive OEMs have been developing increasingly sophisticated strategies to minimise the impact that combustion engines have on the environment. Intelligent thermal management systems to actively control coolant flow around the engine have a positive impact on friction generated in the power cylinder by improving the warmup rate of cylinder liners and heads. This increase in temperature results in an improved frictional performance and cycle averaged fuel consumption, but also increases the piston to liner clearances due to rapid warm up of the upper part of the cylinder head. These increased clearances can introduce piston slap noise and substantially degrade the NVH quality to unacceptable levels, particularly during warmup after soak at low ambient temperatures. Using analytical techniques, it is possible to model the thermo-structural and NVH response of the power cylinder with different warm up strategies.

The sound sources of modern road vehicle can be classified into three components, driving sound (sound generated through normal driving patterns and events), operating sound (sound generated through actuated components not related to driving), and generated synthetic sound (electronic warning / interactive feedback). The characteristic features of these sounds are dependent upon customer expectation and usage requirements. Additional development complexities are introduced due to each market's cultural and regional differences. These differences in preference must be considered for the establishment of the target sound quality in the early vehicle development process. In this paper, a sound quality goal setting procedure based on user preference is introduced. The sound targets are created as a result of the user preference investigation and validated by intercultural comparison.

Tire tread pattern noise is a major source of road noise generated by motor vehicles. Recently, noise control technology has been developing, and low-noise motor vehicles, such as electric vehicles and hybrid vehicles, have been commercialized. The importance of low-noise tires has increased since regulations R117 for tire noise and R51.03 for motor vehicle noise have been strengthened. To evaluate the tire noise in the development stage of motor vehicles, finished products of tires are required; hence, financial and time costs should be invested. Therefore, it is highly useful to predict tire noise levels in the early stages. Recently, a technology to predict the tire pattern noise using a supervised training method of artificial neural network (ANN) has been developed. The tire tread depth is estimated using the shading of the full image of the actual tire, and the leading edge of the contact patch is calculated using tire contact patch images.

Recently, automobile manufacturers are interested in the development of battery electric vehicle (BEV) having a longer mileage to satisfy customer needs. The BEV with high efficiency depends on the temperature of the electric components. Hence it is important to study the effect of the cooling system in electric vehicle in order to optimize efficiency and performance. In this study, we present a 1-D vehicle thermal management (VTM) simulation model. The individual vehicle subsystems were modeled including cooling, power electric (PE), mechanical, and control components. Each component was integrated into a single VTM model and it would be used to calculate energy transfer among electrical, thermal, and mechanical energy. As a result, this simulation model predicts a plenty of information including the state of each component such as temperature, energy consumption, and operating point about electric vehicle depending on driving cycles and environmental conditions.

In this study it will show, big data analysis and user survey of driving records were conducted to investigate frequency of use and ease of operation of the regen paddle to control one-pedal driving system in electric vehicle. According to 3.8 million driving record big data analysis result, it was found that the driver manipulates 3.31 times on average during a single trip, mainly during the early stages of driving. According to user observation research result in 41.8% of participants did not used or used less than 5 time of regen paddle during one single trip. Also 336 participants, which occupy 83%, responded that the regen paddle manipulation for one-pedal driving was inconvenient. In conclusion, because of the use frequency of the regen paddle is low and the operation of regen paddle is inconvenient. It seems necessary to change the design of the regen paddle.

In recent years, the automobile industry has been making efforts to develop vehicles that satisfy customers' emotions rather than malfunctions. The Vehicle Dependability Study(VDS) has been strengthened emotion items since the introduction of the new evaluation system VDS3 from 2015. The ratio of emotion items increased from 11% to 25%. In order to clarify the problem and cause of emotion items, we analyzed verbatim which is the customers' complaint data provided by J.D power every year, but it was difficult to extract customers' intention because the number of verbatim is small and expressed in terms of customer’s term rather than engineer’s term. To solve the problem, we are additionally colleting big data such as internet, warranty, online survey. Since the amount of data is very large, we developed textmining techniques such as dictionary, topic, Support Vector Machine(SVM), n-gram to improve process.