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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.

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.

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.

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

As CO2 emissions from vehicles is gaining a global attention the low fuel consuming power-train is in much greater demand than before. Some alternatives are suggested but the HSDI diesel engine would be the most realistic solution. Vehicle simulation shows that low fuel consuming car can be realized by applying 1∼1.2L HSDI diesel engine in vehicles weighing about 750kg. While the direct injection diesel engine has been researched for a long time enhancement of mixing between air and fuel in a limited space makes it challenging area to develop a small swept volume HSDI diesel engine. We are investigating small HSDI diesel engine combustion technologies as an effort to realize low fuel consuming vehicle. Our main objective in this study is to have a better understanding of the combustion related parameters from such a small size HSDI diesel engine in order to improve engine performance.

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.

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 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 electrical power system is the vital lifeline to most of the control systems on modern vehicles. The demands on the system are highly complex, and a detailed understanding of the system behavior is necessary both to the process of systems integration and to the economic design of a specific control system or actuator. The vehicle electric power system, which consists of two major components: a generator and a battery, has to provide numerous electrical and electronic systems with enough electrical energy. 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. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study.

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.

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.

This paper proposes an effective nonlinear bicycle model including longitudinal, lateral, and yaw motions of a vehicle. This bicycle model uses a simplified piece-wise linear tire model and tire force tuning algorithm to produce closely matching vehicle trajectory compared to real vehicle for wide vehicle operation ranges. A simplified piece-wise tire model that well represents nonlinear tire forces was developed. The key parameters of this model can be chosen from measured tire forces. For the effects of dynamic load transfer due to sharp vehicle maneuvers, a tire force tuning algorithm that dynamically adjusts tire forces of the bicycle model based on measured vehicle lateral acceleration is proposed. Responses of the proposed bicycle model have been compared with commercial vehicle dynamics model (CarSim) through simulation in various vehicle maneuvers (ramp steer, sine-with-dwell).

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.

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.