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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.

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.

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.

For a complete automotive HVAC system, it is desirable to keep good air quality control for the interior vehicle cabin. This experimental study for evaluating the CO2 concentration levels in a vehicle cabin was done on the roads in South Korea. Increasing levels of CO2 can cause a passenger to become tired, sleepy and cause headaches or discomfort. The study results shows that CO2 and fine dust concentration is a result of the number of passengers,_driving condition and HVAC user settings. The result from this investigation can be used to establish a development guide for air quality in a vehicle cabin.

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.

The engine indicated torque is not delivered entirely to the wheels, because it is lowered by losses, such as the pumping, mechanical friction and front auxiliary power consumption. The front auxiliary belt drive system is a big power consumer-fueling and operating the various accessory devices, such as air conditioning compressor, electric alternator, and power steering pump. The standard fuel economy test does not consider the auxiliary driving torque when it is activated during the actual driving condition and it is considered a five-cycle correction factor only. Therefore, research on improving the front end auxiliary drive (FEAD) system is still relevant in the immediate future, particularly regarding the air conditioning compressor and the electric alternator. An exertion to minimize the auxiliary loss is much smaller than the sustained effort required to reduce engine friction loss.

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.

Generally, the HVAC system of a vehicle is composed of Blower unit assembly and Heater unit assembly, and is located on the driver’s side of the dash panel. However, electric vehicles have far fewer parts than conventional internal combustion engine vehicles, so electric vehicles have large space in the engine room. This allows HVAC, which occupies large volume in the interior side, to be pushed in the direction of the engine room altogether, or by placing a part inside the engine room to make a slim cockpit and expand the interior space. However, this new structure, called the Split HVAC System, is mounted through the dash, allowing noise to pass through relatively easily. Since this adversely affects the NVH of an electric vehicle, it needs to be developed in terms of noise transmission. Therefore, in this paper, a study was conducted to predict the sound transmission loss of Split HVAC through an analytical method.

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.

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.

The shift towards electric vehicles is gaining pace to address carbon neutrality and environmental concerns. New technologies are being developed to cater to the unique features of EVs, such as the low indoor noise at low speeds, which require a low-noise ventilation system. A new dual-blower type system was developed to solve the problem of seat-bottom package caused by battery placement in the vehicle. This system uses two blowers, one for the cushion and one for the back, and reduces RPM to lower high-frequency noise. A new solution was introduced for temperature drop performance in the ventilation system. An integrated controller was also developed to control the seat warmer and ventilation system, with a smart control function added to respond to vehicle speed and ventilation time based on customer usage. As a result, this new ventilation system improves air volume, reduces noise, improves foot space, and reduces the number of parts compared to the previous system.

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.

This study has been conducted to analyze microbial diversity and its community by using a method of NGS(Next generation sequencing) technique that is not rely on cultivation for microbial community in an core evaporator causing odor of car air conditioner. The NGS without any cultivation method of cultivation, has been developed recently and widely. This method is able to research a microorganism that has not been cultivated. Differently with others, it can get a result that is closer to fact, also can acquire more base sequence with larger volume in relatively shorter time. According to bacteria population analysis of 23 samples, It can be known limited number of bacteria can inhabit in Evaporator core, due to small exposure between bacteria and evaporate, as well as its environmental characteristics. With the population analysis, only certain group of it is forming biofilm in proportion.

Monitoring driver thermal stress is an integral step for developing an automated climate control function. In this experimental study, various physiological measures for driver’s thermal stress were tracked while intentionally by altering thermal conditions of the seat with a seat air conditioning system (ACS) in summer and a seat heating system (HS) in winter. It was aimed to determine reliable physiological measures for identifying the changes in thermal status induced by the two seat climate control systems. In the first experiment, twenty experienced drivers drove a comfortable sedan for 60 minutes on a real highway while varying the intensity of the seat ACS every 10 minutes to incur ‘hot’ – ‘cool’ – ‘hot’ – ‘cool’ thermal stress. In the second experiment, a new group of eighteen drivers drove the same highway for 30 minutes while increasing the intensity of seat HS to incur ‘cold’ to ‘warm’ thermal stress.

It is an important factor in electric vehicles to show customers how much they can drive with the energy of the remaining battery. If the remaining mileage is not accurate, electric vehicle drivers will have no choice but have to feel anxious about the mileage. Additionally, the potential customers have range anxiety when they consider Electric Vehicles. If the remaining mileage to drive is wrong, drivers may not be able to get to the charging station and may not be able to drive because the battery runs out. It is important to show the remaining available driving range exactly for drivers. The previous study proposed an advanced model by predicting the remaining mileage based on actual driving data and based on reflecting the pattern of customers who drive regularly. The Bayesian linear regression model was right model in previous study.

The steering system is a critical component for controlling a vehicle's direction. In the context of Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, where drivers may not always be actively holding the steering wheel, early detection of precursor noise signals is essential to prevent serious accidents resulting from the loss of steering system functionality. It is therefore imperative to develop a device capable of early detection and notification of steering system malfunctions. Therefore, the current study aimed to quantify the noise levels generated within the Column-based Electric Power Steering (C-EPS) system of a D-segment sedan. To this end, we measured the uniaxial acceleration in nine noise-generating areas while simultaneously collecting data from three Controller Area Network (CAN) sources that are directly related to steering operation.

The existing FCEV have been developed with only a few vehicle models. With the diversification of both passenger and commercial FCEV lineups, as well as the increasing demand for vehicle trailer towing, there is a growing need for high-capacity fuel cell stacks to be applied in vehicles. However, at the current level, there are limitations and issues that arise, such as insufficient power output and reduced driving speed. As a results, the importance of thermal energy management has been increasing along with the increase in required power. Traditional cooling performance enhancement methods have mainly focused on developing increased hardware specifications, but even this approach has reached its limitation due to package, cost and weight problem. Therefore, it is essential to develop a new cooling system to solve the increases in heat dissipation.

Despite the widespread adoption of lithium-ion batteries in various applications such as energy storage, concerns related to thermal management have been persisting, primarily due to the heat generated during their operation and the associated adverse effects on its efficiency, safety, and lifetime. Hence, the thermal characterization of lithium-ion batteries is essential for optimizing the layout of the battery cells for a pack design and the corresponding thermal management system. This study focuses on an experimental investigation of heat generation of Li-ion batteries under different operating conditions, including charge-discharge rates, ambient temperatures, states of charge, and compressive pressure. The experiments were conducted using a custom-designed multifunctional calorimeter, enabling precise measurement of the heat generation rate of the battery and the entropy coefficient. The measured results have shown a good match with the calculated heat generation rate.

In recent years, the automotive industry has been making efforts to develop vehicles that satisfy customers’ emotions rather than malfunctions by improving the durability of vehicles. The durability and reliability of vehicles sold in the U.S. can be determined through the VDS (Vehicle Dependability Study) published by JD Power. The VDS is index which is the number of complaints per 100 units released by J.D. POWER in every year. It investigates customers who have used it for 3 years after purchasing a new car and consists of 177 specific problems grouped into 8 categories such as PT, ACEN, FCD, Exterior. The VDS-4 has been strengthened since the introduction of the new evaluation system VDS-5 in 2015. In order to improve the VDS index, it is important to gather various customer complaints such as internet data, warranty data, Enprecis data and clarify the problem and cause. Enprecis data is survey of customer complaints by on-line in terms of VDS.