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.

CAI (Controlled Auto Ignition) combustion is already well known to be advantageous over conventional cycles in that it facilitates higher engine efficiency and has low emission characteristics. The CAI combustion process is mainly governed by in-cylinder RGF (Residual Gas Fraction), therefore achieving good control of in-cylinder RGF is essential in the development of CAI combustion engine. Usually, in-cylinder RGF controlled via low lift cam, short valve duration and negative valve overlap. More importantly on the other hand, accurate and instantaneous prediction of RGF must be done as a prerequisite to control. However, on-line prediction of RGF is not always practical due to the requirement of expensive fast response exhaust gas analyzers in the empirical case or otherwise due to theoretical models which are just too slow for application by means of simulation solving. In this paper, a newly enhanced theoretical model for predicting on-line in-cylinder RGF is introduced.

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.

Emissions regulations are becoming more severe, and they remain a principal issue for vehicle manufacturers. Many engine subsystems and control technologies have been introduced to meet the demands of these regulations. For diesel engines, combustion control is one of the most effective approaches to reducing not only engine exhaust emissions but also cylinder-by-cylinder variation. However, the high cost of the pressure sensor and the complex engine head design for the extra equipment are stressful for the manufacturers. In this paper, a cylinder-pressure-based engine control logic is introduced for a multi-cylinder high speed direct injection (HSDI) diesel engine. The time for 50% of the mass fraction to burn (MFB50) and the IMEP are valuable for identifying combustion status. These two in-cylinder quantities are measured and applied to the engine control logic.

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.

This paper presents NVH optimization procedure for the 2.5L I4 common rail diesel engine. Distinctive design feature is the low noise timing chain system which realized by chain case modification and meshing noise improvement. The former was effective for reduction of sound level and the later was for sound quality. Combustion excitation force, vibration transmission in engine structure were also improved and countermeasured to achieve powerful and comfortable Sports Utility Vehicle.

Conventional combustion models are suitable for predicting flame propagation for a wrinkled flamelet configuration. But they cannot predict the burned gas composition. This causes the overestimation of burned gas temperature and pressure. A modified method of combustion simulation was established to calculate the chemical composition and to investigate their ultimate fate in the burned gas region. In this work, the secondary products of combustion process, like CO and H2, were considered as well as the primary products like CO2 and H2O. A 3-dimensional CFD program was used to simulate the turbulent combustion and a zero dimensional equilibrium code was used to predict the chemical composition of burned gas. With this simple connection, more reasonable temperature and pressure approaching the real phenomena were predicted without additional time costs.

Automotive companies are trying to enhance the customer’s impression by improving engine sound quality. The target of this sound quality is to create a brand sound that is preferred by their customers as well as quietness of interior noise. Over the past decade there have been many studies in the field of automotive sound quality. These have included the technologies such as tuning of intake orifice and exhaust orifice, tuning of structure-borne, intake feedback devices, active exhaust valves, ANC (Active Noise Cancellation) and ASD (Active Sound Design). The three elements of the sound that affect the feeling of the customer are known as engine order arrangement, frequency balance, and linearity. Here, the most important thing in sound quality development is the order arrangement.

The combustion noise of a diesel engine can be deteriorated by combustion characteristics such as the maximum rate of heat release and the start of combustion. These combustion characteristics in turn are influenced by the factors such as the engine NVH durability, driving conditions, environmental factors and fuel properties. Therefore, we need to develop the robust combustion noise that is insensitive to these factors. To achieve this aim, methods for predicting combustion characteristics has been developed by analyzing the vibration signal measured from the engine cylinder block. The closed-loop control of injection parameters through combustion characteristics prediction has been performed to produce the desired engine combustion performance. We constructed an ECU logic for the closed-loop control and verified the design in a diesel passenger car. We also evaluated the effect of combustion noise and fuel consumption by applying the closed-loop control.

As global emission standards are becoming more stringent, it is necessary to increase thermal efficiency through the high compression ratio in spark-ignited engines. Various studies are being conducted to mitigate knocking caused by an increased compression ratio, which requires an understanding of the combustion phenomena inside the combustion chamber. In particular, the in-cylinder flow is a major factor affecting the entire combustion process from the generation to the propagation of flames. In the field of spark-ignited engine research, where interest in the concept of lean combustion and the expansion of the EGR supply is increasing, flow analysis is essential to ensure a rapid flame propagation speed and stable combustion process. In this study, the flow around the spark plug was measured by the Laser Doppler Velocimetry system, and the correlation with combustion in spark-ignited engines was analyzed.

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.

In this study, fundamental questions in improving thermal efficiency of spark-ignition engine were revisited, regarding two principal factors, that is, stroke-to-bore (S/B) ratio and valve timings. In our experiment, late intake valve closing (LIVC) camshaft and variable valve timing (VVT) module for valve timing control were equipped in the single-cylinder, direct-injection spark-ignition (DISI) engine with three different S/B ratios (1.00, 1.20, and 1.47). In these three setups, displacement volume and compression ratio (CR) were fixed. In addition, the tumble ratio for cylinder head was also kept the same to minimize the flow effect on the flame propagation caused by cylinder head while focusing on the sole effect of changing the S/B ratio.

The high-frequency whining noise produced by motors in modern electric vehicles causes a significant issue, leading to annoyance among passengers. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack other noises to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this study, we explored the application of artificial intelligence to optimize the NVH performance of motors during the design phase. Firstly, we selected and modeled three benchmark motor types using Motor-CAD. Machine learning models were trained using Design of Experiment methods to simulate batch runs of Motor-CAD inputs and outputs.