Search Results

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.

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 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.

As environmental problems such as global warming are emerging, regulations on automobile exhaust gas are strengthened and various exhaust gas reduction technologies are being developed in various countries in order to satisfy exhaust emission regulations. Exhaust gas recirculation (EGR) technology is a very effective way to reduce nitrogen oxides (NOx) at high combustion temperatures by using EGR coolers to lower the combustion temperature. This EGR cooler has been mass-produced in stainless steel, but it is expensive and heavy. Recently, high efficiency and compactness are required for the EGR cooler to meet the new emission regulation. If aluminum material is applied to the EGR cooler, heat transfer efficiency and light weight can be improved due to high heat transfer coefficient of aluminum compared to conventional stainless steel, but durability is insufficient. Therefore, the aluminum EGR cooler has been developed to enhance performance and durability.

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.

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.

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.

Environmental and fuel economy regulations (Eu 6d and WLTP RDE) on automobiles have been tightened recently. To counter this regulation, the global automobile industry is focusing on weight reduction, fuel efficient turbo charger, cooled EGR, thermal management, low friction and so on. However, the high-speed turbocharger makes turbulence, and resulting in airflow noise. This noise is transmitted indoor through the air intake system, which adversely affects the vehicle's competitiveness. Therefore, for turbo engine, it is essential to reduce the noise of the air intake system. The air intake system consists of air cleaner, air filter, air intake hose and air duct. The air flow noise of turbo-engine is mainly the emission noise emitted from the walls of air intake system. And the transfer path of turbo noise is in order of air intake hose, air cleaner and air duct. Therefore, it is effective to reduce the noise of the air intake hose located at the beginning of noise transfer path.

Worldwide projections anticipate a fast-growing market share of the battery electric vehicles (BEVs) to meet stringent emissions regulations for global warming and climate change. One of the new challenges of BEVs is the effective and efficient thermal management of the BEV to minimize parasitic power consumption and to maximize driving range. Typically, the total efficiency of BEVs depends on the performance and power consumption of the thermal management system, which is highly affected by several factors, including driving environments (ambient temperature and traffic conditions) and driver's behavior (aggressiveness). Therefore, this paper investigates the influence of these factors on energy consumption by using a comprehensive BEV simulation integrated with a thermal management system model. The vehicle model was validated with experimental data, and a simulation study is performed by using the vehicle model over various traffic scenarios generated from a traffic simulator.

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.

As a result of stringent global regulations on fuel economy and CO2 emissions, the development of high-efficiency SI engines is more urgent now than ever before. Along with advanced techniques in friction reduction, many researchers endeavor to decrease the B/S (bore-to-stroke) ratio from 1.0 (square) to a certain value, which is expected to reduce the heat loss and enhance the burning rate of SI engines. In this study, the effects of B/S ratios were investigated in aspects of efficiency and knock characteristics using a single-cylinder LIVC (late intake valve closing) GDI (gasoline direct injection) engine. Three B/S ratios (0.68, 0.83 and 1.00) were tested under the same mechanical compression ratio of 12:1 and the same displacement volume of 0.5 L. The head tumble ratio was maintained at the same level to solely investigate the effects of geometrical changes caused by variations in the B/S ratio.

A need to develop a cooling method with high cooling performance like jet impingement is increased as high power of an inverter is required. Jet Impingement on the dimpled plate would increase thermal performance than that of flat plate. Many previous researchers have dealt with the multi jet impingement on flat plate and some results of the study on dimpled plate evaluate the effect on heat transfer coefficients on several limited cases, making it difficult to apply them to inverter designs. Therefore, in this paper, heat transfer performance, pressure drop, and robustness at micro-scale of jet impingement on the dimpled plate were investigated in detail and the correlations of each performance were proposed. Finally, the optimal design was presented. The cooling performance was influenced by the jet array and the effect of depth and width of the dimples.