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In order to understand the automotive PEM fuel cell system, mathematical system modeling is conducted and the model is implemented and simulated by using the Matlab®/Simulink®. The components such as fuel cell stack, air supplier, and radiator are modeled individually and integrated into a system level. The PEM fuel cell system operation control includes thermal management, air supply control, hydrogen supply control, fuel cell stack protection control, and load following control. In the thermal management, the inlet and outlet temperature of coolant are controlled to operate the fuel cell stack in desired temperature range and to prevent flooding inside the fuel cell stack. In air supply control and hydrogen supply control, the flow rates of air and hydrogen are controlled not to starve the fuel cell stack according to the output current. A control structure for the system is developed and confirmed by using the developed simulation model.

Various deformation shapes of the vehicle body were investigated for the purpose to establish vehicle body's performance criteria which correlates well to handling performance and ride comfort. Using CAE tool, the dynamic behavior of a structure by its modal parameter can be described instead of by its nodes and elements. Each modal characteristic in a dynamic system is reduced by its modal stiffness, its modal mass and its damping parameter in the model. This technology offers not only computational efficiency but also parametric model enabling easy what-if simulation. This reduced model can be obtained by modal test as well as simulation of full FE model. It was also investigated that which mode is sensitive to ride or handling performance using the parameterized model. The body stiffness of the brand new 2010 SONATA was improved on reference to the sensitivity analysis. The ride and handling performance of the 2010 SONATA were verified by computer simulation and vehicle field test

Accelerated simulation of vehicle corrosion in a controlled environment not only involves large chambers for actual vehicle tests, but also requires careful consideration of interactions between various parameters given a short time period within which the test is bounded. A new corrosion durability test mode reproducing various field conditions using salt spray, climatic, sunlight simulation and cold chambers has been developed. Verification of the test mode is carried out using four actual vehicle corrosion tests correlated against used cars of Nort h America and Northern Europe. The process of new corrosion test mode is discussed along with the characteristics of the test chambers.

In this study, a co-operative regenerative braking control algorithm was developed for an electric vehicle (EV) equipped with an electronic wedge brake (EWB) for its front wheels and an electronic mechanical brake (EMB) for its rear wheels. The co-operative regenerative braking control algorithm was designed considering the road friction characteristic to increase the recuperation energy while avoiding wheel lock. A powertrain model of an EV composed of a motor, and batteries and a MATLAB model of the control algorithm were also developed. They were linked to the CarSim model of the vehicle under study to develop an EV simulator. The EMB and EWB were modeled with an actuator, screw, and wedge to develop an EMB and EWB simulator. A co-simulator for an EV equipped with an EWB for the front wheels and an EMB for the rear wheels was fabricated, composed of the EV and the EMB and EWB simulator.

This study investigates how hilly road profiles affect the optimal energy management strategy for fuel cell hybrid electric vehicle (FCHEV) with various battery sizes. First, a simplified FCHEV model is developed to describe power and energy flows throughout the powertrain and evaluate hydrogen consumption. Then, an optimal control problem is formulated to find the globally optimal energy management strategy of FCHEV over driving cycles with road elevation profile. In order to solve the optimal energy management problem of the FCHEV, Dynamic Programming, a dynamic optimization method, is used, and their results are analyzed to find out how hilly road conditions affect the optimal energy management strategies. The results show that the optimal energy management with a smaller battery tends to actively prepare (e.g. pre-charge/pre-discharge) for uphill/downhill roads in order not to violate the battery state of charge (SoC) bounds.

Recently, increasing system complexity and various customer demands result in the need for highly efficient vehicle development processes. Once the brake torque is predicted accurately during the driving scenario in the earlier stage, it will be able to prevent the changing the vehicle or brake system design to satisfy the legal regulation and customer requirement. As brake torque performance target allocate brake pad friction coefficient level and characteristic, the accurate friction coefficient prediction should be preceded for accurate prediction for brake torque. Generally, the friction coefficient of the brake pad is known to vary nonlinearly depending on the physical properties of the disc and the pad, as well as the brake disc rotational speed, the disc temperature, and the hydraulic pressure. Furthermore, it varies depending on the driving scenario even when other conditions are the same. Therefore, it is necessary to apply new methods to solve these challenges.

Hyundai Motor Company developed its second-generation fuel cell hybrid electric vehicle (FCEV) based on its small Tucson SUV. Compared to Hyundai's first generation fuel cell vehicle, the Santa Fe FCEV, the Tucson FCEV has an extended driving range plus cold weather starting capability. It incorporates numerous technical advances including a fuel cell that operates at sub-zero temperatures and a new high voltage lithium ion polymer battery. Using both a fuel cell and a high voltage battery as sources for driving energy, the Tucson hybrid system provides optimum driving conditions, which ensures high tank to wheel efficiency. The Tucson FCEV's power plant has been located in the front - under the front hood - unlike its predecessor Santa Fe FCEV, which featured an under-floor installation. More importantly, Tucson FCEV's driving range has been extended to 300km thanks to its 152-liter hydrogen storage tanks.

Hyundai motor company has developed a fuel cell hybrid vehicle that has ultra-capacitors as a secondary power source. The simulation of fuel cell vehicles allows the user to analyze various types of fuel cell systems and hybrid configurations before implementing into a real system and to reduce the development time and cost. Before implementing fuel cell vehicles, a fuel cell vehicle simulation model, that has component modularity and forward facing characteristics, was developed. The simulation model was used in designing the fuel cell hybrid vehicle to select component sizes and a hybrid configuration. The hybridization by using ultra-capacitors provided better fuel economy and power response than the hybridization by using batteries.

Bad weather conditions such as torrential rain, heavy snow, and thick fog frequently occur worldwide. Vehicle accidents in such bad weather conditions account for a significant portion of all vehicle accidents, and the level of damage is relatively severe compared to other accidents that occur in clear weather. This paper analyzes the driver's driving stability in bad weather conditions, which has such a significant meaning, in various ways through experiments on the inconvenience experienced by the driver. In this study, three levels of bad weather conditions were implemented in a driving simulator environment to evaluate driver inconvenience for six activities. Through driving experiment, quantitative bio-signals and vehicle signals were analyzed in each weather condition. The SD survey was used to assess the driver's inconvenience level for activities performed while driving and analyze the ranking of inconvenience.

Expanding various future mobilities such as purpose built vehicle (PBV), urban air mobility (UAM), and robo-taxi, the application of autonomous driving system (ADS) technology is also spreading. The main point of ADS is to ensure safety by monitoring vehicle anomalies to prevent functional failure or accident. In this study, a model-based diagnosis and prognosis process was established using degradation data generated during autonomous driving simulation. A vehicle model was designed using Modelica/Dymola, and autonomous driving simulation was performed by integrating the lane keeping assistant (LKA) system with the vehicle model using Matlab/Simulink. Degradation data for the 3 components (a shock absorber damper, a suspension bush, and a tire) of the chassis system were input into the integrated simulation model. The degradation behavior was monitored with K-nearest neighbor (K-NN) and Gaussian mixture model (GMM).

The electric power system of a modern vehicle has to supply enough electrical energy to numerous electrical and electronic systems. The electric power system of a vehicle consists of two major components: a generator and a battery. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. In order to avoid the over/under design problem of the electric power system, an easy-to-use and inexpensive simulation program may be needed. In this study, a vehicle electric power simulator is developed. The simulator can be utilized to determine the optimized capacities of generators and batteries appropriately. To improve the flexibility and easy usage of the simulation program, the program is organized in modular structures, and is run on a PC.

In the view point of driving safety, the crosswind sensitivity of a vehicle becomes more important, as the driving speed in highway gets higher in these days. The sensitivity of a vehicle to crosswind depends on many factors, including the design of the suspension and aerodynamics of the body, etc. However, the knowledge about this phenomenon has still to be improved, in order to develop vehicle with optimum characteristics for crosswind stability. In this research, the physics behind the sensitivity of a vehicle is discussed in detail through various kinds of virtual test using computer aided engineering (CAE) simulation scheme. In the first, a reliable simulation model for vehicle, driver, wind generator and interactions among them is built. This simulation model is verified by comparison with test results of real vehicle. Then, the sensitivity analysis is carried out to find out the most influential design parameters.

The subject of this study is a centrifugal compressor for Fuel Cell Electric Vehicles (FCEV). Recently there is a growing interest in FCEVs since they are considered a realistic solution to environmental regulations for passenger cars to reduce emissions. Water vapor is the only byproduct of a reaction in the Proton Electrolyte Membrane (PEM) fuel cell stack which generates electricity with oxygen from the surrounding air and hydrogen from a fuel tank. Auxiliary systems called Balance of Plant (BOP) serve to provide air and hydrogen to the stack in a correct ratio. The compressor is one of key components of this system because compression of the intake air brings an increase in efficiency and power density of the FCEV. This paper presents the characteristics of a 10 kW class centrifugal compressor with an oil-free bearing system. It consists of a shaft, two airfoil journal bearings and a pair of thrust bearings.

The existing FCEV have been developed with only a few vehicle models. With the diversification of both passenger and commercial FCEV lineups, as well as the increasing demand for vehicle trailer towing, there is a growing need for high-capacity fuel cell stacks to be applied in vehicles. However, at the current level, there are limitations and issues that arise, such as insufficient power output and reduced driving speed. As a results, the importance of thermal energy management has been increasing along with the increase in required power. Traditional cooling performance enhancement methods have mainly focused on developing increased hardware specifications, but even this approach has reached its limitation due to package, cost and weight problem. Therefore, it is essential to develop a new cooling system to solve the increases in heat dissipation.