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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.

Computer Aided Control System Design (CACSD) tools are widely used in the development of embedded control systems. Automatic code generation for CACSD models is the subject of increasing interest. In this study, Software-in-the-Loop Simulation (SILS) and Rapid Control Prototyping (RCP) are proposed as a development framework for the design of real-time control systems. SILS is a simulation environment to consider functional behavior as well as temporal behavior of control systems. RCP supports seamless development from design to implementation through automatic code generation. SILS/RCP environments make it possible to design and analysis control systems under conditions similar to real execution during off-line simulation and to realize controllers in the early design phase.

A computer aided test system, which is called MOde Survey System (MOSS), is newly developed to evaluate a driving pattern and traffic flow in Seoul, Korea. This system is designed for the people who work on vehicle emissions and energy more quantitatively with the aim of being cost-effective and easy-to-use. Compared to currently-existing Test and Measurement Systems, MOSS is designed and developed for a specific goal with a couple of unique features. These features are: 1) To be able to be used as either a stand alone system like a data logging system or a real-time processing system with a PC to easily visualize vehicle performances and traffic information during the test. 2) To provide a statistical analysis program for easy use to analyze of driving pattern and traffic situation with logged test data files.

An evidential theory is widely used for 2D grid-based localization in a robotics field because the theory has benefits to consider additional states such as 'unknown' and 'conflict'. However, there are some problems such as computational limitation and excessive resource share when the localization system is expanded from 2D grid to 3D voxel. In order to overcome the problems, this paper proposes the parallelized particle filter based localization system using 3D evidential voxel maps. A many-core processor based parallel computing framework with optimization techniques is applied to accelerate the computing power. Experiments were performed to evaluate the performance of the localization system in a complex environment, and to compare the computational time and resources between various types of processing units. The experimental results show that the proposed parallel particle filter is much more efficient than particle filter without parallel computing regarding computational cost.

In spark ignition engines, the mechanism of transferring electrical energy from an ignition system into the mixture in the spark gap is controlled by many aspects. The major parameters of these aspects are inputs of electrical energy, combustion energy release, and heat transfers. Heat caused by combustion energy is transferred to the spark plug, cylinder head, unburned mixture, and others. This study presents the development and validation of a flame kernel initiation and propagation model in SI engines, and most of the aspects described above are considered during the course of the model development. Furthermore, the model also takes into account the strain rate of the initial kernel and residual gas fraction. The model is validated by the engine experiments, which are conducted in a constant volume combustion chamber.

With fuel efficiency becoming an increasingly critical aspect of internal combustion engine (ICE) vehicles, the necessity for research on efficient generation of electric energy has been growing. An energy management (EM) system controls the generation of electric energy using an alternator. This paper presents a strategy for the EM using a control mode switch (CMS) of the alternator for the (ICE) vehicles. This EM recovers the vehicle’s residual kinetic energy to improve the fuel efficiency. The residual kinetic energy occurs when a driver manipulates a vehicle to decelerate. The residual energy is commonly wasted as heat energy of the brake. In such circumstances, the wasted energy can be converted to electric energy by operating an alternator. This conversion can reduce additional fuel consumption. For extended application of the energy conversion, the future duration time of the residual power is exploited. The duration time is derived from the vehicle’s future speed profile.

In this paper, a nonlinear dynamic engine model is introduced, which is developed to represent an SI engine over a wide range of operating conditions. The model includes intake manifold dynamics, fuel film dynamics, and engine rotational dynamics with transport delays inherent in the four-stroke engine cycles, and can be used for designing engine controllers. The model is validated with engine-dynamometer experimental data. The accuracy of the model is evaluated by the comparison of the simulated and the measured data obtained from a 2.0 L inline four-cylinder engine over wide operating ranges. The test data are obtained from 42 operating conditions of the engine. The speed range is from 1500 (rpm) to 4000 (rpm), and the load range is from 0.4 (bar) to WOT. The results show that the simulation data from the model and the measured data during the engine test are in good agreement.

The introduction of inexpensive cylinder pressure sensors provides new opportunities for precise engine control. This paper presents a control strategy of spark advance and air-fuel ratio based upon cylinder pressure for spark ignition engines. In order to extend the cylinder pressure based engine control to a wide range of engine speeds, the appropriate choice of control parameters is important as well as essential. For this control scheme, peak pressure and its location for each cylinder during every engine cycle are the major parameters for controlling the air-fuel ratio and spark timing. However, the conventional method requires the measurement of cylinder pressure at every crank angle degree to determine the peak pressure and its location. In this study, the peak pressure and its location were estimated, using a multi-layer feedforward neural network, which needs only five cylinder pressure samples at -40°, -20°, 0°, 20°, and 40° after TDC.

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.

Cylinder air charge is an important parameter to reduce generation of visible emissions by adjusting the amount of fuel injected into a diesel engine. In this study, we propose a cylinder air charge estimation algorithm for a diesel engine equipped with variable geometry turbocharger (VGT), exhaust gas recirculation (EGR), and swirl control valve (SCV). The estimation algorithm predicts the cylinder air charge using a mean value air path model and measurable signals available in mass produced engines. The estimation algorithm addresses effects of the VGT, EGR, and SCV on the cylinder air charge. The proposed estimation algorithm was validated with a 1-D engine model simulation.

This paper presents a start of combustion (SOC) control for a common rail direct injection (CRDI) diesel engine, which is achieved by utilizing in-cylinder pressure signals. The difference pressure (DP), which is the difference between the in-cylinder firing pressure and motoring pressure, is selected as the variable for SOC detection. An adaptive feedforward controller was applied in order to improve the performance of the feedback controller. The feedforward controller consists of the radial basis function network (RBFN) and the feedback error learning method that is for training of the network. In this paper, the RBFN has two inputs which are engine speed and target SOC, and has one output, start of energizing. The feasibility and performance of the proposed controller were validated by transient engine operation experiments.

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.

In order to evaluate vehicle powertrain performances and driver behaviors, a computer aided in-vehicle data acquisition system named MOde Survey System (MOSS) is newly developed in conjunction with a motor manufacturer. MOSS is designed to be used by personnel related to vehicle emissions and energy with the aim of being cost-effective and easy-to-use. Since driving behaviors and patterns influence powertrain performance in terms of fuel economy and emissions, engineers can utilize the system for understanding the driving pattern and traffic situation quantitatively. MOSS mainly consists of an MCU-based hardware and PC-based software. MOSS logs and analyzes various data related to vehicle driving. Compared to currently-existing Test and Measurement Systems, MOSS is designed and developed for a specific goal with several unique features.

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.

The development of autonomous vehicle requires the state-of-the-art technologies in perception, planning, control, and system integration. This paper presents an overview of the system architecture and software architecture of autonomous vehicles for system integration. Network based system architecture in this paper provides a distributed computing system for autonomous driving. Further, a real-time path planning and a target speed generation are described based on the curvilinear coordinate system. The design of a path in the curvilinear coordinate system stretches the design space as like the Cartesian coordinate system to simplify the generation of the path. In determination of target speed, curvatures and risk of a generated path were utilized for safe autonomous driving.

The effect of ignition energy, ignition system and spark plug electrode on initial flame kernel development in a constant volume combustion chamber has been studied. The experiment was done in a quiescent and lean condition. Two different ignition systems are designed and evaluated, and several kinds of spark plugs are also made. The spark time controller is also developed to regulate dwell time and to synchronize ignition time with data acquisition time. The ignition energy is measured at each experimental condition, and the flame propagation is measured by piezoelectric type pressure sensor. The heat release rate and the mass fraction burnt are derived from the combustion pressure. The results show that as the dwell time or the spark plug gap are increased, the ignition energy is increased, which derives higher heat release rate and faster the mass fraction burnt.

FlexRay is a deterministic and fault-tolerant in-vehicle network(IVN) protocol. It is expected to become a practical standard for automotive communication systems. According to the FlexRay protocol specifications, there are about 60 configurable parameters which should be determined in the design phases. The parameters increase the complexities of FlexRay-based control system development. In this study, we are suggesting a formal design process for FlexRay-based control systems, which is focused on network parameter optimization. We introduce design phases from functional system models to implementations. These phases present formal ways for task allocation, node assignment, network configuration, and implementations. In the network configuration phase, two FlexRay core parameters are selected to optimize network design. Optimal methods of the core parameters provide concise guide lines for optimal communication cycle length and optimal static slot length.

In this paper, we proposed a formalized design procedure for networked control systems (NCSs). In a conventional development of NCSs, well-designed control algorithms do not result in the intended control performance after an implementation due to time delays, such as network-induced delays and controller computation delays. The proposed design procedure shows how to minimize the degradation of the control performance caused by the time delays. The design procedure was verified by designing a network-based traction control system (TCS). The designed TCS was realized and tested by using a rapid control prototyping (RCP) platform and a hardware-in-the-loop simulation (HILS) environment.

In a multi-cylinder variable valve lift (VVL) engine, in spite of its high efficiency and low emission performance, operation of the variable valve lift brings about not only variation of the air-fuel ratio at the exhaust manifold, but also individual cylinder air-fuel ratio maldistribution. In this study, in order to reduce the air-fuel ratio variation and maldistribution, we propose an individual cylinder air-fuel ratio estimation algorithm for individual cylinder air-fuel ratio control. For the purpose of the individual cylinder air-fuel ratio estimation, air charging dynamics are modeled according to valve lift conditions. In addition, based on the air charging model, individual cylinder air-fuel ratios are estimated by multi-rate sampling from single universal exhaust gas oxygen (UEGO) sensor located on the exhaust manifold. Estimation results are validated with a one-dimensional engine simulation tool.

In this paper, we proposed an estimation model for the Indicated Mean Effective Pressure (IMEP) which means the generated torque by the combustion with using only a single cylinder pressure sensor. The IMEP of each cylinder leads the rotational crankshaft acceleration. Based on the rotational dynamics, we can determine an empirical model structure between IMEP and crankshaft acceleration to estimate the IMEP of an individual cylinder. The proposed model calculates the IMEP of an individual cylinder by applying the IMEP obtained from a single pressure sensor and crankshaft acceleration. Consequently, the proposed estimation method can be used for combustion control with cost affordable equipment. In addition, it is beneficial for a real-time system because the calculation time of IMEP of other cylinders can be eliminated. The proposed model is validated through the engine experiment.