Search Results

As data emerges as the most valuable resource in the world, the evolution of the related data industry is progressing faster. In this study, we tried to discover effective factors for fuel cell durability by using big data analysis techniques with accumulated vehicle actual road data (de-identified Blue Link Data). Basic analysis is performed assuming factors that are expected to have a significant impact on the fuel cell durability performance, and durability factor modeling according to the clustering between driving patterns and durability performance is used to determine. Now can see the change in durability performance. By analyzing the correlation between each driving pattern and durability performance, it is possible to know the weight of the effective factor affecting the durability. If the effective factor with high weight is improved in the actual vehicle unit, the durability performance is expected to increase, and the effect will be verified through real road operation.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

As CO2 legislation tightens, the next generation of turbocharged gasoline engines must meet stricter emissions targets combined with increased fuel efficiency standards. Recent studies have shown that the following technologies offer significant improvements to the efficiency of turbocharged GDI engines: Miller Cycle via late intake valve closing (LIVC), low pressure loop cooled EGR (LPL EGR), port water injection (PWI), and cylinder deactivation (CDA). While these efficiency-improving technologies are individually well-understood, in this study we directly compare these technologies to each other on the same engine at a range of operating conditions and over a range of compression ratios (CR). The technologies tested are applied to a boosted and direct injected (DI) gasoline engine and evaluated both individually and combined.

As CO2 legislation tightens, the next generation of turbocharged gasoline engines must meet stricter emissions targets combined with increased fuel efficiency standards. Promising technologies under consideration are: Miller Cycle via late intake valve closing (LIVC), low pressure loop cooled exhaust gas recirculation (LPL EGR), port water injection (PWI), and cylinder deactivation (CDA). While these efficiency improving options are well-understood individually, in this study we directly compare them to each other on the same engine at a range of operating conditions and over a range of compression ratios (CR). For this purpose we undertake a comprehensive simulation of the above technology options using a GT-Power model of the engine with a kinetics based knock combustion sub-model to optimize the fuel efficiency, taking into account the total in-cylinder dilution effects, due to internal and external EGR, on the combustion.

In recent years, emission regulations have been getting increasingly strict. In the development of engines that comply with these regulations, in-cylinder pressure plays a fundamental role, as it is necessary to analyze combustion characteristics and control combustion-related parameters. The analysis of in-cylinder pressure data enables the modelling of exhaust emissions in which characteristic temperature can be derived from the in-cylinder pressure, and the pressure can be used for other investigations, such as optimizing efficiency and emissions through controlling combustion. Therefore, a piezoelectric pressure sensor to measure in-cylinder pressure is an essential element in the engine research field. However, it is difficult to practice the installation of this pressure sensor on all engines and on-road vehicles owing to cost issues.

This paper introduces the advancement of Engine Idle Stop-and-Go (ISG, also known as Auto Engine Stop-Start) and Neutral Coasting Control (NCC) with utilizing Advanced Driver Assistance System (ADAS) and GPS. The ISG and the In-Neutral Coasting (also known as Sailing or Gliding) have been widely implemented in recent vehicles for improving their fuel economy. However, many drivers find them somewhat disturbing because they basically change behaviors of their cars from what they used to. This annoyance discourages usages of those functions and eventually undermines their benefit of fuel saving. In order to mitigate the problem, new ISG and NCC algorithms are proposed. As opposed to the conventional logics that rely only on driver’s pedal action, the new algorithms determine whether or not to enable those functions for the given driving condition, based on the traffic information obtained using ADAS sensors and the location data from GPS and navigation map.

The large luxury sedan seat has a 22-way Movement. It offers a wide range of adjustments to enhance passenger comfort performance while it has many constraints on movement in constrained indoor space. In addition, the power seat is operated by a motor, which makes it difficult for the user to determine the amount of adjustment, unlike determining the amount of adjustment by the power and feel of a person, such as manual seat adjustment. IMS, one-touch mode, is also constrained by parameters such as indoor space package, user's lifestyle, etc. during function playback. This paper aims to design the seat control logic to achieve the best seat comfort while satisfying each constraint. The results of this study are as follows. Increase robustness of power seat control logic. Provide optimal adjustments and comfort at each location. Offer differentiated custom control and seating modes for each seat. Improve customer satisfaction and quality by upgrading software.

Numerical investigation of engine performance and emissions of a six-stroke gasoline compression ignition (GCI) engine combustion at low load conditions is presented. In order to identify the effects of additional two strokes of the six-stroke engine cycle on the thermal and chemical conditions of charge mixtures, an in-house multi-dimensional CFD code coupled with high fidelity physical sub-models along with the Chemkin library was employed. The combustion and emissions were calculated using a reduced chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Two power strokes per cycle were achieved using multiple injections during compression strokes. Parametric variations of injection strategy viz., individual injection timing for both the power strokes and the split ratio that enable the control of combustion phasing of both the power strokes were explored.

Although subjective measurements are critical for qualifying seat comfort in terms of good or bad, objective measurements are the basis for quantifying these differences and ultimately controlling seat comfort performance through engineering design specs, targets, and/or guidelines. Many objective automotive seat comfort tools and techniques used today are based on methods derived in the past. This paper examines the engineering problems and solutions that make these historical influences relevant today. Particular focus is given to design considerations for the A-surface, B-surface, and the compressed surface of the seating system.

Due to improvements in vehicle powertrain performance, friction material fade performance is becoming an important topic. For this reason, needs for studies to improve thermal characteristics of the brake system is increasing. Methods for improving the fade characteristics have several ways to improve the thermal characteristic of friction materials and increase disc capacity. However, increasing disc capacity(size) have some risk of weight and cost rise, and friction factor improvements in friction material tend to cause other problems, such as increasing squeal wire brush noise and increasing metal pick up on disc surface. Therefore, a slot disc study is needed to overcome the problems discussed previously. Currently, there is few research history for slot disc related to fade and metal pickup improvements.

Voice Recognition (VR) systems have become an integral part of the infotainment systems in the current automotive industry. However, its recognition rate is impacted by external factors such as vehicle cabin noise, road noise, and internal factors which are a function of the voice engine in the system itself. This paper analyzes the VR performance under the effect of two external factors, vehicle cabin noise and the speakers’ speech patterns based on gender. It also compares performance of mid-level sedans from different manufacturers.

A vehicle simulation model is developed, validated and integrated into a closed-loop virtual driving environment using a state-of-the-art hexapod driving simulator. Thirty variant states are implemented and evaluated subjectively on steering and handling performance quality and quantity. Standard open-loop objective testing manoeuvres are simulated and performance metrics are calculated, allowing for a systematic cross-correlation process. Graphical analysis of the correlation metrics proves that chassis changes may accurately be felt through the simulator interface. It is proposed how obtained correlation models may serve for driver-feel optimizing target setting in early vehicle development stages, frontloading a great deal of costly prototype testing. System requirements are established and benefits and limitations are portrayed.

Currently, diesel engine-out exhaust NOx emission level prediction is a major challenge for complying with the stricter emission legislation and for control purpose of the after-treatment system. Most of the NOx prediction research is based on the Zeldovich thermal mechanism, which is reasonable from the physical point of view and for its simplicity. Nevertheless, there are some predictable range limitations, such as low temperature with high EGR rate operating conditions or high temperature with low EGR rates. In the present paper, 3 additional considerations, pilot burned gas mixing before the main injection; major NO formation area; concentration correction, were applied to the previously developed real-time NO estimation model based on in-cylinder pressure and data available from ECU. The model improvement was verified on a 1.6 liter EURO5 diesel engine in both steady and transient operation.

Polylactide (PLA), which is one of the most important biocompatible polyesters that are derived from annually renewable biomass such as corn and sugar beets, has attracted much attention for automotive parts application. The manufacturing method of PLA is the ring-opening polymerization of the dimeric cyclic ester of lactic acid, lactide. For the PLA composites including stereocomplexed with L- and D-PLA, we developed the unit processes such as fermentation, separation, lactide conversion, and polymerization. We investigated D-lactic acid fermentation with a view to obtaining the strains capable of producing D-lactic acid, and through catalyst screening test for polycondensation and depolymerization reactions, we got a new method which shortens the whole reaction time of lactide synthesis step. Poly(d-lactide) is obtained from the ring-opening polymerization of d-lactide. Also we investigated several catalysts and polymerization conditions.

This paper focuses on the vehicle test result of the US fuel economy test cycles such as FTP75, HWY and US06 with model based Cooled EGR system. Cooled EGR SW function was realized by Model Based Development (internal rapid prototyping) using iRPT tool. With EGR, mixing exhaust gas with clean air reduces the oxygen concentration in the cylinder charge, as a result, the combustion process is slowed, and the combustion temperature drops. This experiment confirmed that the spark timing was more advanced without knocking and manifold pressure was increased in all cases with EGR. A positive potential of fuel economy improvement on FTP mode, US06 mode have seen in this experiment but not for HWY where the engine load is quite low and the spark advance is already optimized. As a result, fuel economy was increased by maximum 3.3% on FTP, 2.7% on US06, decreased by 0.3% on HWY mode respectively with EGR.

Creep groan noise occurs in a just moving vehicle by the simultaneous application of torque to the wheel and the gradual release of brake pressure in-vehicle. It is the low frequency noise giving the driver a very uncomfortable feeling. It is caused by the stick-sleep phenomenon at the lining and disc interface. Recently, the field claim of low frequency creep groan has increased. There are a lot of efforts to improve creep groan noise by means of modification of lining material. In this paper, Transfer path of creep groan noise was analyzed through ODS and TPA. Additionally the correlation between Source (Brake torque variation, Brake vibration) and Creep Groan Sound level was discussed. Finally countermeasure to Creep Groan noise was suggested.

Electro-Mechanical Brake (EMB) is the brake system that is actuated by electrical energy and has a similar design with the Electric Parking Brake (EPB). It uses motor power and gears to provide the necessary torque and a screw & nut mechanism is used to convert the rotational movement into a translational one. The main difference of EMB compared with EPB is that the functional requirements of components are much higher to provide the necessary performance for service braking such as response time. Such highly responsive and independent brake actuators at each wheel lead to enhanced controllability which should result in not only better basic braking performance, but also improvements in various active braking functions such as integrated chassis control, driver assistance systems, or cooperative regenerative braking.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

A new approach to achieve better customer perception of overall vehicle quietness is the sound balance improvement of vehicle interior sound during driving. Interior sound is classified into 3 primary sound source shares such as engine sound relative to revolution speed, tire road noise and wind noise relative to vehicle speed. Each interior sound shares are classified using the synchronous time-domain averaging method. The sound related to revolution order of engine and auxiliaries is considered as engine sound share, tire road noise and wind noise shares are extracted by multiple coherent output power analysis. Sound balance analysis focuses on improving the relative difference in interior sound share level between the 3 primary sound sources. Virtual sound simulator which is able to represent various driving conditions and able to adjust imaginary sound share is built for several vehicles in same compact segment.

In the early stage of vehicle development process, it is customary to establish a set of goals for each kinematic and compliance (K&C) characteristic and try to find out design variables such as the location of hard points and bushing stiffness which can achieve these goals. However, since it is very difficult to find out adequate set of design variables which satisfy all the goals, many engineers should rely on their own experiences and intuitions, or repeat trial and error to design a new suspension and improve old one. In this research, we develop a suspension design process by which suspension K&C characteristic targets can be achieved systemically and automatically. For this purpose, design optimization schemes such as design of experiments (DoE) and gradient-based local optimization algorithm are adopted.