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Wide attention to fuel cell electric vehicles (FCEVs) comes from two huge issues currently the world is facing with: the concern of the petroleum reserves depletion due to consequent oil dependence and the earth global warming due in some extent to vehicle emissions. In this background, Hyundai, along with its sister company Kia, has been building the FCEVs and operating their test fleet with several tens of units at home and abroad. Since 2004, 32 passenger vehicles have been offered for the Department of Energy's controlled hydrogen fleet and infrastructure demonstration and validation project in the U.S. In the meantime, from 2006, 30 passenger vehicles as well as four buses, featuring the in-house developed fuel cell stack and its associated components, are currently under the domestic operation for the FCEV learning demonstration led by the Ministry of Knowledge and Economy.

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.

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.

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.

The series-parallel hybrid electric vehicle(HEV), which employs a planetary gear set to combine one internal combustion engine(ICE) and two electric motors(EMs), can take advantages of both series and parallel hybrid system. The efficient powertrain operating point of the system can be obtained by the instantaneous optimization of equivalent fuel consumption. However, heavy computational requirements and variable constraints of the optimization process make it difficult to build real-time control strategy. To overcome the difficulty, this study suggests the control strategy which divides the optimization process into 2 stages. In the first stage, a target of charge/discharge power is determined based on equivalent fuel consumption, then in the second stage, an engine operating point is determined taking power transfer efficiency into account.

In this paper, a design procedure for the optimized light weight front cross member, which is a sub frame of the car chassis, without sacrificing basic functional requirements is presented. As the first step, optimal structural integrity was calculated and extracted using a CAE technique with the available volume constraint of the package layout. Quantitative design loads for the cross member was achieved by measurement. Dynamic load analysis using ADAMS was also performed to determine the loads. Later, these calculated loads were applied to the FEM stress analysis of the cross member. Furthermore, durability analysis was also performed using load profile database measured from ‘Hyundai Motor Co. Proving Ground’. Four constant amplitude durability tests and two static tests were performed on the cross member prototypes to confirm design reliability.

Supervisory control strategy of a hybrid electric vehicle (HEV) provides target powers and operating points of an internal combustion engine and an electric motor. To promise efficient driving of the HEV, it is needed to find the proper values of control parameters which are used in the strategy. However, it is very difficult to find the optimal values of the parameters by doing experimental tests, since there are plural parameters which have dependent relationship between each other. Furthermore variation of the test results makes it difficult to extract the effect of a specific parameter change. In this study, a model based parameter optimization method is introduced. A vehicle simulation model having the most of dynamics related to fuel consumption was developed and validated with various experimental data from real vehicles. And then, the supervisory control logic including the control parameters was connected to the vehicle model.

Due to technological evolutions and social demands, motor vehicles are requested to be enhanced in terms of occupant safety and comfort. As a result, many countries are reinforcing crash regulations and new car assessment programs. Automotive seats are essential parts for providing passenger safety and comfort and have become most important. Many automotive companies concentrate on optimization of the seat structure. This paper presents an overview of the recent evolution of the seat structures and gives a development procedure covering seat frame design, optimization and validation. Through the study, a competitive frame design is drawn as a case result and a design guideline and a standard development procedure is established

A technical approach to reduce NOx and to minimize the fuel consumption caused by the DeNOx aftertreatment system was introduced. The NEDC mode test of the HMC (Hyundai Motor Company) DeNOx system was done with a Euro 5 vehicle (ETW (Equivalent Test Weight) = 1,810 kg, 143 kW, 430 N⋅m), which resulted in that the Euro 6 legislation standards were met. The NOx and HC emissions were, respectively, measured to be 0.059 g/km and 0.087 g/km with the hydrothermal-aged catalysts, and CO₂ was increased by ≺ 4%.

Due to aging of a battery over lifetime, the rated power and nominal energy capacity will be reduced compared with the initial rated power and capacity. These result in influences on the vehicle driving performance and fuel economy. To monitor and diagnose the aging of the battery, in this paper, the method of predicting the available rated power and energy capacity of Li-ion battery under in-vehicle condition is proposed. Under constant power test, available power is calculated from the estimated parameters using recursive least square method. Further, available energy capacity is evaluated through SOH(cn) defined by the ratio of initial state-of-charge (SOC) variation to present SOC (\GdSOC ⁿ /ΔSOC ⁿ ) variation under arbitrary in-vehicle driving cycles. To verify the proposed method, experiments for aging Li-ion battery are performed in hybrid electric vehicle.

This paper reflects an efficient and comprehensive approach for vehicle sound optimization integrated into the entire development process. It shows the benefits of early consideration of typical vehicle NVH features and of intensive interaction of P/T and vehicle responsibilities. The process presented here considers the typical restriction that acoustically representative prototypes of engines and vehicles are not available simultaneously at the early development phase. For process optimization at this stage, a method for vehicle interior noise estimation is developed, which bases on measurements from the P/T test bench only, while the vehicle transfer behavior for airborne and structure-borne noise is assumed to be similar to a favorable existing vehicle. This method enables to start with the pre- optimization of the pure P/T and its components by focusing on such approaches which are mainly relevant for the vehicle interior noise.

Hyundai has developed a Santa Fe fuel cell vehicle (FCV) in which methanol fuel processor is installed and integrated with PEM fuel cell system. Pure hydrogen is produced from the mixture of methanol and water by steam reforming followed by metal membrane purification and is then fed to fuel cell system to generate electrical energy. This system has the advantage of simplifying the integration of fuel cell subsystem and fuel processor subsystem. The operation of brassboard system has been carried out for performance evaluation and the development of fuel cell controller. And then the methanol reforming fuel cell system has been incorporated into electric drive train in the vehicle. AC induction motor is powered by the hybrid system using fuel cell and a nickel metal hydride battery as energy sources to improve the system efficiency and the acceleration response of the vehicle.

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.

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 nano-sized PM and THC emission characteristics were investigated according to the fuel injection strategy such as a pressure and timing in the GDI engine. On the part-load condition, the particulate emissions exhibited a strong sensitivity to the injection timing. The fuel injection pressure also had a great association with the nano-particles and THC. A size of PM exhausted from the GDI engine located near 10nm on the part-load. In contrast, accumulation mode particles within 60 - 80nm mainly exhausted during the cold transient start phase. Increment of fuel injection pressure positively affected on the nano-particle and THC emissions during the start of the engine, as well.

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.

Engine calibration on the powertrain test bed with transient mode is proposed with dynamic powertrain test bed having low inertia dynamometer. Automated ECU (Engine Control Unit) calibration system is completed with the combination of experimental design software, powertrain test bed, evaluation tools and their electrical interfaces. The process is composed up of the system interface definition, test design using DoE skill, test proceedings by step sequence of connecting systems, measured data collecting, mathematical model and optimization result extraction at the end. All the processes are automated by interfaces between the systems. Acceleration surge is minimized by proposed process by optimizing combustion control labels and tip in driveability is maximized by manipulating torque filter labels of EMS (Engine Management System) logic. Their detailed steps from the problem definition to the verification test results of improved design with vehicle test are presented.

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.