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A body joint is one of the most major factors affecting the overall body stiffness in a body system. Thus, in order to optimize the body system, the joint must be also optimized. In order to optimize a body joint, it is necessary to first identify the efficiency of the joint itself. Then, the joint stiffness targets for each joint must be set by analyzing the interaction between joint stiffness and overall body stiffness and the function of the joint in terms of vehicle performance. Finally, an optimal joint structure should be designed with an optimal design methodology. In this study, an optimal methodology for the joint stiffness and design is introduced. Based on this research, an optimized joint design for each joint was applied to the new SUV model resulting in a lightweight body with a required body stiffness.

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.

This paper presents an energy-optimal deceleration planning system (EDPS) to maximize regenerative energy for electrified vehicles on deceleration events perceived by map and navigation information, machine vision and connected communication. The optimization range for EDPS is restricted within an upcoming deceleration event rather than the entire routes while in real time considering preceding vehicles. A practical force balance relationship based on an electrified powertrain is explicitly utilized for building a cost function of the associated optimal control problem. The optimal inputs are parameterized on each computation node from a set of available deceleration profiles resulting from a deceleration time model which are configured by real-world test drivings.

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.

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.

The sliding surface of the brake friction material is not uniform but composed of random contact plateaus with a broad pressure distribution, which are known to closely related to the triggering mechanism of friction induced noise and vibrations. The non-uniform contact plateaus are attributed to the various ingredients in the friction material with a broad range of physical properties and morphology and the size and stiffness of the plateau play crucial roles in determining the friction instability. The incorporation of friction surface inhomogeneity is, therefore, crucial and has to be counted to improve the accuracy of the numerical calculation to simulate brake noise. In this study, the heterogeneous nature of the friction material surface was employed in the simulation to improve the correlation between numerical simulations and experimental results.

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.

This paper aims to establish a systematic process of developing a brand driving sound. Firstly, principal factors of a brand sound identity are extracted from factor analysis of many sample cars. As a result, brand sound positioning map is drawn using jury test data. Also, the multiple regression analysis of subjective and objective test results is carried. As a result, the principal factors are expressed by objective test data and brand sound positioning map can be easily updated from the measurement data. In addition, what should be improved for designing a target sound is reviewed. Secondly, various technologies of target sound design are discussed to involve the brand identity and vehicle’s character in driving sound. Also, an efficient tool to implement the target sound with an active sound design (ASD) system in a vehicle is introduced. This tool enables to efficiently design, tune and simulate a target sound for ASD system in a laboratory.

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.

An integrated starter and generator (ISG) is a type of electric machine which is mechanically connected to an internal combustion engine (ICE). The ISG is intended to conduct important roles in the hybrid electric vehicle (HEV) such as engine start and stop. Since the HEV has frequent electric vehicle (EV)/HEV mode transition, rapid engine cranking and vibration-free engine stop controls are necessary. In the case of the engine stop, the ISG provides the negative torque output to the ICE which can rapidly escape from its resonance speed. However, the ISG torque is determined by engineering intuition, the amount of energy recovery is hardly considered. Dynamic programming (DP) is an effective solution to find optimal ISG control strategy to maximize energy recovery during engine stop transition. Even though DP is an offline algorithm, the result can be used as a reference to evaluate and improve an existing on-line algorithm.

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.

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.

Customer vehicle usage monitoring is one of the most fundamental elements to consider in the process of developing a durable vehicle. The extant method to research customer vehicle usage takes considerable time and effort because it requires attaching a series of sensors to the vehicle-gyroscope, accelerometer, microphone, and GPS-to gather information through data logs and then to analyze data in a computer where designated analyzing software has been installed. To solve the problem, this paper introduces a new concept of integrated system developed to examine customer vehicle usage that can analyze data by collecting it from a variety of sensors installed on a smartphone.

This work studied the control technique for the engine clutch engagement at launch for the TMED parallel HEV for the improved drivability and dynamic performance. Analysis are done on the speed synchronization of the clutch plates, the speed control using the starter motor (ISG), and the fluid pressure control for the clutch. Possible external factors such as changes in the friction coefficient of transmission fluid, temperature variation, auxiliary power and pressure losses are identified and their effects on the targeted dynamic performance are examined. The targeted system performance was achieved with a learning control technique using fluid pressure as the only control input. This involves the compensation for the effect of external factors on the fluid pressure profile and this effect is memorized for the subsequent slip-launch application.