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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.

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.

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.

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 squeak noise generated during the moving of the door glass has a influence on the performance of vehicles felt by the consumer. In order to improve the noise, it is necessary to understand the principle of a friction vibration. In this paper, it is confirmed that the principle on the waist belt is most closely related to stick-slip and sprag-slip among various vibration characteristics. Stick-slip is expressed by energy accumulation and divergence due to difference in static and dynamic friction coefficient. Sprag-slip define instability of geometric structure due to angle of lips on the belt. In this paper, the physical model and the energy equation are established for the above two phenomena. Stick-slip can be solved by decreasing the difference of the static and dynamic friction coefficient. Sprag-slip is caused by the ratio of compressive and shear stiffness of the lips. The belt uses flocking to ensure durability, not coating.

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.

Owing to the enhanced performance of engines these days, more heat should be dissipated in the braking system. Failure of doing this properly causes temperature rise in the brake disc which result in the brake fade, disc distortion, brake judder, etc. A cooling-air-duct was proposed as a solution to prevent these from happening. In this paper, we present our work based on experiments optimized parameters such as direction, location, shapes and the size of the duct for the cooling-air-duct installation in real cars. We installed the duct extended from a front bumper to a rear wheel guard. Experimental parameters were compared with theoretical analysis using the impinging jet analysis. The heat transfer coefficients were determined by using the finite elements method (FEM). We found that our experimental data is supportive of theoretical analysis. We believe that our results should serve an useful guideline for designing the cooling-air-duct for braking system.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

Numerical durability analysis is the only approach that can be used to assess the durability of vehicles in early stages of development. In these stages, where there are no physical prototypes available, the road wheel forces (or spindle forces) for durability testing on Belgian PG (Proving Ground) must be predicted by VPG (Virtual Proving Ground) or derived from the measured forces of predecessor vehicles. In addition, the tuning parts and geometry are not fixed at these stages. This results in the variation of spindle forces during the development stages. Therefore, it is not reasonable to choose the forces predicted at a specific tuning condition as standard forces. It is more reasonable to determine the standard forces stochastically using the DB of the measured forces of predecessor vehicles. The spindle forces measured or predicted on Belgian PG are typically stationary random.

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.

It is common knowledge that body structure is an important factor of road noise performance. Thus, a high stiffness of body system is required, and determining their optimized stiffness and structure is necessary. Therefore, a method for improving body stiffness and validating the relationship between stiffness and road noise through CAE and experimental trials was tested. Furthermore, a guideline for optimizing body structure for road noise performance was suggested.

In order to achieve the proper automobile interior sound, the tailpipe noise of the exhaust system must be considered as a main contributor. This paper describes a study of the achievement of dynamic sound quality through exhaust system design. Firstly, we determined the vehicle's interior sound quality and established a target sound using a subjective assessment of 10 benchmark vehicles. The exhaust noise target is determined by means of transfer path analysis focusing on the noise source and how it's impacted by the muffler design. The exhaust system is commonly modeled as a combination of source strength and impedance. We obtained the source character by the wave decomposition method using two microphones and six loads ultimately leading to an optimized design of the inner muffler structure. Based on this study, we achieved dynamic interior sound and improved exhaust system performance.

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.

An innovative design process is proposed to be applicable in the early conceptual design phase as a means of front loading design. The objective of the study is to minimize trial and errors in the detailed design phase and to shorten the overall design period. The process includes design optimization which is based on efficient modeling techniques. An integrated CAD/CAE modeling method and a simplified quality FE model are key factors in the course of effectuation. The conceptual modeling takes into account the adaptability of computer-generated models with the use of CAD/CAE integrated design environment. To achieve maximum efficiency in the repeated computations in optimization, an FE modeling approach is introduced in terms of simplicity and quality. The proposed FE modeling employs beam and spring elements to construct vehicle body models, which is targeted to produce an instant analysis result with a robust conceptual design at the incipient phase of development.

In diesel engine development, fuel consumption, emissions and combustion noise have been main development objectives for fuel economy, low emissions and NVH. These main objectives can be achieved with advanced engine technologies. As electronic actuating systems are widely applied on diesel engines, elaborate control is required. This is because the main development targets are greatly affected by engine control parameters but frequently have a trade-off relationship. Therefore, the optimization of combustion control parameters is one of the most challenging tasks for improvement. As an efficient method, the DOE methodology has been used in engine calibration. In order to develop a mathematical model, the input and output values must be measured. Unlike other variables, combustion noise has been continually reported to have better indication method in simplified way. In this paper, advanced noise index from cylinder pressure signal is applied on engine test.

This paper describes how to meet LEVII ULEV70 emission standards and minimize fuel consumption with the combined NOx after-treatment (LNT+SCR) system for diesel vehicles. Through analysis of LNT's functionality and characteristics in a LNT+SCR combined after-treatment system, allowed a new control strategy to be established, different from the existing LNT-only system. In the 200°C or higher condition where SCR can provide the most stable NOx conversion efficiency, rich regeneration of LNT was optimized to minimize LNT deterioration and fuel consumption. Optimized mapping between rapid heat up strategy and raw NOx reduction maximized LNT's NOx conversion efficiency during the intervals when it is not possible for SCR to purify NOx This study used bench aged catalysts which were equivalent to 150K full useful life.

Many high risks of failure in developing and applying new technologies exist in the recent automotive industry because of big volume of selling cars in a global market. Several recalls cost companies more than $ 100 million per problem. New technologies always have uncertainty in performing intended functions at various given conditions despite the fact that engineers do their best to develop technologies to meet all the requirements. Uncertainty of new technologies put companies into danger of failing in their business. Therefore, many companies tend to take interest in reducing risks from the uncertainty in technologies, but the increasing complexity of modern automotive technologies make it difficult to develop complete technologies. A new engineering methodology called SPEED Engineering was introduced to reduce the risks of new technology applications and to facilitate engineers to conceive innovative ideas dominating the market in the future.

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

Currently, the interest in accelerated reliability testing (ART) of electric vehicles parts has been increasing. In particular, an electric motor and battery are vital components of battery powered electric vehicles. The electric motor has two major roles, to discharge or charge battery when it is driven or braking. For analyzing the exact behavior mechanism of electric motor and predicting lithium-ion battery cell degradation, new accelerated reliability testing technology is required. This paper describes the results of research and development in new approach to reliability testing for electric vehicles. The methodology to measure a precise motor output torque of the rotating rotor using telemetry system was provided. The electric energy quantities as well as the used quantities of the electric power were also analyzed. The results of research and development in new approach to reliability testing for electric vehicles were systematized and reflected in development.