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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.

In general, when a problem occurs in a component of powertrains, various phenomena appear, and abnormal noise is one of them. The service mechanics diagnose the noise through analysis by using their ears and equipment. However, depending on their experiences, analysis time and diagnostic accuracy vary greatly. To shorten the analysis time and improve the diagnostic accuracy, we have developed a technology to diagnose powertrain parts that cause abnormal noises. To create the best deep learning model for our diagnosis, we tried to collect many abnormal noises from various parts. The collected noise data was measured under idle and various operating conditions from our vehicles and test cells. This noise data is abnormal noises generated from engines, transmissions, drive system and PE (Power Electric) parts of eco-friendly vehicles. From the collected data, we distinguished good and bad data through detailed analysis in time and frequency domain.

An important trend among vehicle NVH engineers is the production of attractive engine acceleration sound quality for the enhancement of a vehicle's image and performance. In addition, customers have increasing interest and enjoyment in customizing their cars to reflect their personal taste and preferences. The PESS (Personalized Engine Sound System) has been developed for making a unique and individually customizable vehicle concept. The system allows the customers an opportunity to create a variety of engine sounds in a single vehicle using active sound design technology. In this system, three different engine sound concepts are pre-defined, Dynamic, Sporty, and Extreme. Each of the engine sounds can then be adjusted with parameters that determine the timbre, such as main order, rumble, and high order. In addition, the pedal position during acceleration has also been used as a parameter to further personalize the experience.

CO2 emission is more serious in recent years and automobile manufacturers are interested in developing technologies to reduce CO2 emissions. Among various environmental-technologies, the use of solar roof as an electric energy source has been studied extensively. For example, in order to reduce the cabin ambient temperature, automotive manufacturers offer the option of mounting a solar cell on the roof of the vehicle [1]. In this paper, we introduce the semi-transparent solar cell mounted on a curved roof glass and we propose a solar energy management system to efficiently integrate the electricity generated from the solar roof into internal combustion engine (ICE) vehicles. In order to achieve a high efficiency solar system in different driving, we improve the usable power other than peak power of solar roof. Peak power or rated power is measured power (W) in standard test condition (@ 25°C, light intensity of 1000W/m2(=1Sun)).

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.

Pressure variation during engine combustion generates torque fluctuation that is delivered through the driveline. Torque fluctuation delivered to the tire shakes the vehicle body and causes the body components to vibrate, resulting in booming noise. HKMC (Hyundai Kia Motor Company)’s TMED (Transmission Mounted Electric Device) type generates booming noises due to increased weight from the addition of customized hybrid parts and the absence of a torque converter. Some of the improvements needed to overcome this weakness include reducing the torsion-damper stiffness, adding dynamic dampers, and moving the operation point of the engine from the optimized point. These modifications have some potential negative impacts such as increased cost and sacrificed fuel economy. Here, we introduce a method of reducing lock-up booming noise in an HEV at low engine speed.

A Light Detection And Ranging (LiDAR) is now becoming an essential sensor for an autonomous vehicle. The LiDAR provides the surrounding environment information of the vehicle in the form of a point cloud. A decision-making system of the autonomous car is able to determine a safe and comfort maneuver by utilizing the detected LiDAR point cloud. The LiDAR points on the cloud are classified as dynamic or static class depending on the movement of the object being detected. If the movement class (dynamic or static) of detected points can be provided by LiDAR, the decision-making system is able to plan the appropriate motion of the autonomous vehicle according to the movement of the object. This paper proposes a real-time process to segment the motion states of LiDAR points. The basic principle of the classification algorithm is to classify the point-wise movement of a target point cloud through the other point clouds and sensor poses.

High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles.

An efficient development environments such as Software-in-the-Loop Simulation (SILS) and Rapid Control Prototyping (RCP) have been widely used to reduce the development time and cost of real-time ECUs. However, conventional SILS does not consider temporal behaviors caused by computation time, task scheduling, network-induced delays, and so on. As a result, the control performance of ECU is likely to be degraded after implementation. To overcome this problem, SILS/RCP which considers the temporal behaviors was suggested in the previous research. In this study, we validated the proposed SILS/RCP environments which are used to design an Electronic Stability Control (ESC) system which is one of the hard real-time control systems. The proposed SILS/RCP environments make it possible to realize ECUs in the early design phase by considering temporal behaviors.

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.

Passenger fatigue during long distance driving is greatly influenced by the comfort performance of the seat. Seat comfort performance is determined by the appropriate contour of the seat and the appropriate pad with sufficient thickness. The height of vehicle has been lowered to enhance car styling, and battery for electric vehicle applied to the underbody of the vehicle, reducing the package space of the seat in the vehicle. These external factors eventually lead to a reduced pad thickness of the seat cushion and compromise one of the important components in the seat cushion compartment, creating an uncomfortable cushioning problem when driving long distances. To improve the cushion composition of the seat within a limited package, air bladders are applied to the underside of the cushion pad. In addition, the function to support the buttocks using the air bladders of the lower cushion, similar to lumbar support for the back, was implemented to improve cushion comfort performance.

The software must be verified and optimized from time to time to ensure system performance quality from the development process. Because the later you discover performance issues, the greater the cost of performance improvements, along with the extent to which they are fixed in the source code. In particular, performance problems due to poor system design should be identified and corrected as soon as possible. Also, as development progresses, source code added for new features and modified by bugs can potentially increase system resource usage or worsen responsiveness. Therefore, the development process needs to periodically measure, analyze, and improve system performance. This paper introduces the system-wide performance analyzer and explains how to use it to measure and analyze the performance of the infotainment system for performance management and improvement.

The windshield is an integral part of almost every modern passenger car. Combined with current developments in the automotive industry such as electrification and the integration of lightweight material systems, the reduction of interior noise caused by stochastic and transient wind excitation is deemed to be an increasing challenge for future NVH measures. Active control systems have proven to be a viable alternative compared to traditional passive NVH measures in different areas. However, for windshield actuation there are neither comparative studies nor actually established actuation concepts available to the automotive industry. This paper illustrates a comparative conceptual study on windshield actuation for the active control of wind noise in a passenger car. Making use of an experimental modal analysis of the windshield installed in a medium-sized vehicle, a reduced order numerical simulation model is derived.

This paper introduces a systematic wiring guideline which includes coupling noise calculation, wire layout design, and wire type selection methodologies. The coupling theory between wires has been introduced long time ago but it was not successfully applied to real automotive wiring design due to the complexity in the theory such as large number of parameters and many different conditions in automotive wiring environment. In this paper, the complexity is reduced by separating physical parameters and electrical parameters and identifying controllable parameters and given parameters. This paper first introduces parameters which are used in the coupling equations and automotive wiring design, then the coupling noise calculation method which uses the coupling equations is introduced. The systematic automotive wiring guideline which prevents noise problem in various design stage such as system filter design, wire layout design, wire type selection is introduced.

The alternator provides power to vehicle electrical loads with the battery, and its maximum current depends on various factors such as electrical load, engine speed, thermal condition, and other variables. Above all, thermal effects make alternator simulations more complicated. For example statically similar conditions may show different results according to the temperature variation for each alternator operation. This paper proposes a two-stage statistically-based model structure which separates dynamic thermal effects from steady state performance. The method was validated by experiments and shows good predictive performance, suitable for use in test reduction.

Controlled Auto-Ignition (CAI) combustion is a new combustion concept. Unlike the conventional internal combustion engine, CAI combustion takes place homogeneously throughout the fuel/air mixture with self ignition, and the mixture is burned without flame propagation. The start of combustion (SOC) is a critical factor in the combustion because SOC affects exhaust gas emissions, engine power, fuel economy and combustion characteristics. This paper presents a control oriented SOC detection method using a 10 bar of difference pressure, and proposes 50 percent normalized difference pressure for SOC detection parameter. Difference pressure is defined as the difference between the in-cylinder firing pressure and the in-cylinder motoring pressure. These methods were determined by CAI combustion experiments. Managing the difference pressure is a fast and precise method for SOC detection.

In CRDI diesel engines, the piezo injector is gradually replacing the solenoid injector due to the quick response of the actuator. Operating performance of the injectors in the CRDI diesel engine has an influence on engine emissions. Therefore, accurate injector control is one of the most important parts of the CRDI engine control. The objective of this paper is the development of a piezo injector driver for CRDI diesel engines. Electrical characteristics of the piezo injector were analyzed. A control strategy for charging and discharging the actuator are proposed. The developed injector driver is verified by experiments under various fuel pressures, injection durations and driving circuit voltages.

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 a model based sensor fault detection and isolation algorithm for the vertical acceleration sensors of the Continuous Damping Control (CDC) system, installed on the sprung mass. Since sensor faults of CDC system have a critical influence on the ride performance as well as the vehicle stability, the sensor fault detection algorithm must be implemented into the overall CDC algorithm. In this paper, each vertical acceleration sensor installed on the sprung mass (two in the front corners and one in the rear) separately estimates the vertical acceleration of the center of gravity of the sprung mass. Then, the sensor fault is detected by cross-checking all three vertical acceleration estimates independently obtained by the each vertical acceleration sensor.

The paper presents a new offset compensation method of a yaw rate sensor and a lateral acceleration sensor. It is necessary to compensate the offsets of the analog sensors, such as the yaw rate sensor and the lateral acceleration sensor, to acquire accurate signals. This paper proposes two different offset compensation algorithms, the sequential compensation method and the model based compensation method. Both algorithms are combined with the algorithm map depending on the vehicle driving status. The proposed algorithm is verified by the computer simulations.