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The purpose of this paper is to develop and experimentally validate a practical and effective technique for the automatic regulation of a hydraulic semiactive vibration absorber (SAVA) for automobiles. The work relies on a consistent hydraulic model of the actuator dynamics that includes the effects of fluid compressibility and a nonlinear viscous loss characteristic. A bistate control algorithm is developed using a Lyapunov approach that seeks to dissipate the energy of the system. The performance of the proposed semiactive damper design on a quarter car model of an automobile suspension is established experimentally on a vibrating test stand. The work provides evidence that the inexpensive hardware design makes it possible to improve the ride and handling performance.

A fault detection method with parity equations is proposed in this paper. Due to low cost implementation, the velocity of a motor is not measurable in EPB systems. Therefore, residuals are not reliable with a low resolution encoder to estimate the motor velocity. In this paper, we propose a fault detection method with sensorless estimation using current ripples. The method estimates position and velocity of the motor by detecting periodical oscillations of the armature current caused by rotor slots. This method could estimate position and velocity of the motor with less computational effort than a state observer. Moreover, the method is less sensitive to motor parameters than model-based estimation methods. The effectiveness of this method is validated with experimental data. The simulation results show that various faults have their own residual patterns. Therefore, we could detect the fault by monitoring the residual signals.

This paper presents three types of controllers for Electric Parking Brake (EPB) Systems: bang-bang, linear proportional (P), and nonlinear proportional (P) controller. Mechanical and electrical parts of EPB system are modeled and implemented using Modelica language. There is good agreement between simulation and experimental results. For the stability analysis, the EPB system is modeled as a state-dependent switched system with simplified friction dynamics. From simulation and experimental results, it turns out that the nonlinear P controller provides good uniformity in performance and robustness among them.

This work attempts a systematic investigation of the effects of flow maldistribution on the light-off behavior of a monolithic catalytic converter. To achieve this goal, a combined chemical reaction model and three-dimensional computational fluid dynamic modeling technique has been developed. The computational results reveal that the influence of area ratio was significant during high flow transient conditions. The cross-sectional area ratio with the smaller value increases the thermal gradient due to flow maldistribution in the monolith, which degrades performance of catalytic converter. Due to locally concentrated high velocities, large portions of the monolith remain cold and CO,HC are unconverted during warm up period. Therefore, flow maldistribution can cause a significant retardation of the light-off and can eventually worsen the conversion efficiency.

The performance of an integrated Vehicle Stability Control (VSC) system depends on not only control logic itself, but also the performance of state estimator and control threshold. In conventional VSCs, a control threshold is designed by vehicle characteristics and is centered on average drivers. A VSC algorithm with variable control threshold has been investigated in this study. The control threshold can be determined by phase plane analysis of side slip angle and angular velocity. Vehicle side slip angle estimator has been evaluated using test data. Estimated side slip angle has been used in the determination of the control threshold. The performance of the proposed VSC algorithm has been investigated by human-in-the-loop simulation using a vehicle simulator. The simulation results show that the control threshold has to be determined with respect to the driver steering characteristics.

After the COVID-19 pandemic, leisure activities and cultures have undergone significant transformations. Particularly, there has been an increased demand for outdoor camping. Consequently, the need for capabilities that allow vehicles to navigate not only paved roads but also unpaved and rugged terrains has arisen. In this study, we aim to address this demand by utilizing AI to introduce a 'Stuck Probability Estimation Algorithm' for vehicles on off-road. To estimate the 'Stuck Probability' of a vehicle, a mathematical model representing vehicle behavior is essential. The behavior of off-road driving vehicles can be characterized in two main aspects: firstly, the harshness of the terrain (how uneven and rugged it is), and secondly, the extent of wheel slip affecting the vehicle's traction.

This paper presents a closed-loop evaluation of the Vehicle Stability Control (VSC) systems using a vehicle simulator. Human driver-VSC interactions have been investigated under realistic operating conditions in the laboratory. Braking control inputs for vehicle stability enhancement have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. A driving simulator which consists of a three-dimensional vehicle dynamic model, interface between human driver and vehicle simulator, three-dimensional animation program and a visual display has been validated using actual vehicle driving test data. Real-time human-in-the loop simulation results in realistic driving situations have shown that the proposed controller reduces driving effort and enhances vehicle stability.

Intelligent driving assistant systems have been studied meticulously for autonomous driving. When the systems have the responsibility for driving itself, such as in an autonomous driving system, it should be aware of its’ surroundings including moving vehicles and must be able to evaluate collision risk for the ego vehicle's planned motion. However, when recognizing surrounding vehicles using a sensor, the measured information has uncertainty because of many reasons, such as noise and resolution. Many previous studies evaluated the collision risk based on the probabilistic theorem which the noise is modeled as a probability density function. However, the previous probabilistic solutions could not assess the collision risk and predict the motion of surrounding vehicles at the same time even though the motion is possible to be changed by the estimated collision risk.

In response to the stipulations of the Energy Policy and Conservation Act and the global momentum toward carbon mitigation, there has been a pronounced tightening of fuel economy standards for manufacturers. This stricter regulation is coupled with an accelerated transition to electric vehicles, catalyzed by advances in electrification technology and a decline in battery cost. Improvements in the fuel economy of medium- and heavy-duty vehicles through electrification are particularly noteworthy. Estimating the magnitude of fuel economy improvements that result from technological advances in these vehicles is key to effective policymaking. In this research, we generated vehicle models based on assumptions regarding advanced transportation component technologies and powertrains to estimate potential vehicle-level fuel savings. We also developed a systematic approach to evaluating a vehicle’s fuel economy by calibrating the size of the components to satisfy performance requirements.

In this paper, a control oriented cylinder-by-cylinder engine model (CCEM) and ECU-in-the-loop simulation (EILS) of common-rail direct injection (CRDI) diesel engine are presented. The CCEM includes the combustion model of torque production so that it is possible to acquire the in-cycle information, such as cylinder pressure. EILS environment using the CCEM is proposed for cylinder pressure based controller design. It allows real-time engine simulation available, and is applicable for developing the control logic and validating prototype ECUs. Finally, the accuracy of the CCEM is evaluated by the engine experimental data.

The functional requirements (FRs) and design equation of a flexible system change in a continuous manner with respect to a variable such as time. An event driven flexible system is defined as a subcategory of the flexible system in that it changes in a discrete space. A design scenario is developed for the event driven systems. The design equation for each event should be defined by using the axiomatic approach and the design equations are assembled to form a full design equation. The design equation for each event can be established by sensitivity analysis. In conceptual design, the design order is determined based on the full design equation. Design parameters (DPs) are found to satisfy FRs in sequence. A design parameter may consist of multiple design variables. In detailed design, the design variables are determined. The occupant protection system is an event driven flexible system because the design matrix and its elements change according to the impact speed.

Lane keeping assistant system (LKAS) is expected to reduce the driver workload with assisting the driver during driving and is regarded as a promising active safety system. For the proposed LKAS which requires cooperative driving between driver and the assistance system, a Model Based Predictive Controller (MBPC) is proposed to minimize the effect of system overshoot caused by the time delay from the vision-based lane detection system. In order to validate the proposed LKAS controller, a HIL (Hardware In the Loop) simulator is built using steering mechanism, single camera, torque motor, sensors, etc. The performance of the proposed system is demonstrated in various roadways.

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.

Drivers’ physical and physiological states change with prolonged driving. Driving for extended periods of time can lead to an increased risk of low back pain and other musculoskeletal disorders, caused by the discomfort of the seats. Static and dynamic are the two main categories must be considered within the seating development. The posture and orientation of the occupant are the important factors on static comfort. Driving posture measurement is essential for the evaluation of a driver workspace and improved seat comfort design. This study evaluated the comfortable driving posture through physiological and ergonomics measurements of an automotive premium driver seat. The physiological evaluation includes electroencephalographic (EEG) for brain waves, Biopac’s AcqKnowledge program, and subjective measurements on 32 healthy individuals. JACK simulation was used for the ergonomics evaluation, i.e., the magnitude of the spinal loads about lumbar vertebrae was estimated.

Under the present effort to decrease of air pollution, Electric Vehicles (EVs) are appeared and developed. EVs are running by using electrical energy resource by supporting of battery packs. The effect of air-conditioning has proven to be a serious problem to the point of battery depleting. Thus in the present study, effects of air conditioning (i.e., cooling and heating) on driving range were studied for various driving modes including UDDS, HWFET, and NEDC. The result shows that EV energy efficiency is opposing the usual trend of internal combustion engine vehicle's fuel consumption in highway driving mode than urban driving mode. In highway mode, EV energy efficiency and driving range also decease than urban driving mode. This status was influenced on motor characteristic which torque decrease in high speed rotating conditions and highway driving mode consist of constant speed velocity so it couldn't use the regenerative braking system effectively.

Electro-Mechanical Brake (EMB) systems can provide improved braking and stability functions such as ABS, EBD, TCS, ESC, BA, ACC, etc. For the implementation of the EMB systems, reliable and robust fault detection algorithm is required. In this study, a model-based fault detection algorithm is designed based on the analytical redundancy method in order to monitor possible faults in EMB systems. The performance of the proposed model-based fault detection algorithm is verified in simulations. The effectiveness of the proposed algorithm is demonstrated in various faulty cases.

Increasing demands on the emission reduction of high speed direct injection (HSDI) diesel engines require more accurate control of injection parameters such as the injection timing, injection rate, and injection quantity. In order to meet injection requirements, the piezo injector, which has a piezoelectric element as an actuator, has been recently developed. Compared with solenoid-actuated injectors, piezo-actuated injectors yield greater force and give faster response times, resulting in more accurate and faster injections. In this study, a mathematical model of a piezo-actuated injector is developed. The injector model consists of three subsystems: the piezo-actuator subsystem, the mechanical subsystem, and the hydraulic subsystem. The constitutive relations of piezoelectricity are used for modeling the piezo-actuator subsystem. An estimation method of the injection timing and rate is introduced based on the proposed model.

In electronic vehicles (EVs) or hybrid electronic vehicles (HEVs), an inverter system has a direct-current-link capacitor (DC-link capacitor) which provides reactive power, attenuates ripple current, reduces the emission of electromagnetic interference, and suppresses voltage spikes. A film capacitor has been used as the DC-link capacitor in high level power system, but the film capacitor's performance has deteriorated over operating time. The decreasing performance of the film capacitor may cause a problem when supplying and delivering energy from the battery to the vehicle's power system. Therefore, the lifetime prediction of the film capacitor could be one of critical factors in the EVs and HEVs. For this reason, the lifetime and reliability of the film capacitor are key factors to show the stability of the vehicle inverter system. There are a lot of methods to predict the lifetime of the film capacitor.

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.

An important challenge for modeling Direct-Injection Spark-Ignition (DISI) gasoline engines is understanding flash boiling spray. Flash boiling occurs when the ambient pressure is lower than the vapor pressure of the fuel and affects the spray structure and mixture formation process inside an engine. Gasoline is a multi-component fuel and the effects of each component on flash boiling are difficult to estimate. As a preliminary study to investigate the mixture formation process of the flash boiling spray, a single-component fuel was used to validate the flash breakup model. The flash breakup model was applied to KIVA 3V release2. Bubble growth in the drop was modelled by the Rayleigh-Plesset equation. When bubbles grow to satisfy the breakup criterion, breakup occurs and induces a smaller SMD for flash breakup cases. To investigate flash breakup modeling, simulations without the flash breakup model and with the flash breakup model was compared.