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The three major challenges in the power electronics in hybrid and electric vehicles are: System cost, power density and reliability. High temperature power device and packaging technologies increases the power density and reliability while reducing system cost. Advanced Silicon devices with synthesized high-temperature packaging technologies can achieve junction temperature as high as 200C (compared to the present limitation of 150C) eliminating the need for a low-temperature radiator and therefore these devices reduces the system cost. The silicon area needed for a power inverter with high junction temperature capability can be reduced by more than 50 - 75% thereby significantly reducing the packaging space and power device and package cost. Smaller packaging space is highly desired since multiple vehicle platforms can share the same design and therefore reducing the cost further due to economies of scale.

Wide attention to fuel cell electric vehicles (FCEVs) comes from two huge issues currently the world is facing with: the concern of the petroleum reserves depletion due to consequent oil dependence and the earth global warming due in some extent to vehicle emissions. In this background, Hyundai, along with its sister company Kia, has been building the FCEVs and operating their test fleet with several tens of units at home and abroad. Since 2004, 32 passenger vehicles have been offered for the Department of Energy's controlled hydrogen fleet and infrastructure demonstration and validation project in the U.S. In the meantime, from 2006, 30 passenger vehicles as well as four buses, featuring the in-house developed fuel cell stack and its associated components, are currently under the domestic operation for the FCEV learning demonstration led by the Ministry of Knowledge and Economy.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

The newly released Distributed System Interface 3 (DSI3) Bus Standard specification defines three modulation levels form which 16 valid symbols are coded. This complex structure is best decoded with symbol pattern recognition. This paper proposes a simplification of the correlation score calculation that sharply reduces the required number of operations. Additionally, the paper describes how the pattern recognition is achieved using correlation scores and a decoding algorithm. The performance of this method is demonstrated by mean of simulations with different load models between the master and the sensors and varying noise injection on the channel. We prove than the pattern recognition can decode symbols without any error for up to 24dBm.

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.

This paper discusses the RDC method utilizing delta-sigma analog-to-digital converter hardware module (DSADC) integrated in the Infineon's microcontroller family. With its higher resolution capability when compared to the regularly used ADC with successive-approximation (SAR), DSADC seems to have more potential. On the other hand, DSADC's inherent properties, such as asynchronous sampling rate and group delay, which when not handled properly, would have negative effects to the rotor positioning system. The solution to overcome those side-effects involves utilization of other internal microcontroller's resources such as timers and capture units, as well as additional software processing run inside CPU. The rotor positioning system is first modeled and simulated in high-level simulation language environment (Matlab and Simulink) in order to predict the transient- and steady state behaviors. The group delay itself is obtained by simulating the model of DSADC module implementation.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

In-vehicle communication faces increasing bandwidth demands, which can no longer be met by today's MOST150, FlexRay or CAN networks. In recent years, Fast Ethernet has gained a lot of momentum in the automotive world, because it promises to bridge the bandwidth gap. A first step in this direction is the introduction of Ethernet as an On Board Diagnostic (OBD) interface for production vehicles. The next potential use cases include the use of Ethernet in Driver Assistance Systems and in the infotainment domain. However, for many of these use cases, the Fast Ethernet solution is too slow to move the huge amount of data between the Domain Controllers, ADAS Systems, Safety Computer and Chassis Controller in an adequate way. The result is the urgent need for a network technology beyond the Fast Ethernet solution. The question is: which innovation will provide enough bandwidth for domain controllers, fast flashing routines, video data, MOST-replacement and internal ECU buses?

As the original engine sound is usually not enough to satisfy the driver’s desire for a sporty and fascinating sound, Active Noise Control (ANC) and Active Sound Design (ASD) have been great technologies in automobiles for a long time. However, these technologies which enhance the sound of vehicles using loud speakers or electromagnetic actuators etc. lead to the increase of cost and weight due to the use of external amplifiers or actuators. This paper presents a new technology for generating a target sound by the active control of a permanent magnet synchronous motor (PMSM) of a mass-production steering system. The existing steering hardware or motor is not changed, but only additional software is added. Firstly, an algorithm of this technology, called Active Sound Generation (ASG), is introduced which is compiled and included in the ECU target code. Then the high frequency noise issue and its countermeasures are presented.

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.

Recently, vehicle networks have increased complexity due to the demand for autonomous driving or connected devices. This increasing complexity requires high bandwidth. As a result, vehicle manufacturers have begun using Ethernet-based communication for high-speed links. In order to deal with the heterogeneity of such networks where legacy automotive buses have to coexist with high-speed Ethernet links vehicle manufacturers introduced a vehicle gateway system. The system uses Ethernet as a backbone between domain controllers and CAN buses for communication between internal controllers. As a central point in the vehicle, the gateway is constantly exchanging vehicle data in a heterogeneous communication environment between the existing CAN and Ethernet networks. In an in-vehicle network context where the communications are strictly time-constrained, it is necessary to measure the delay for such routing task.

A main challenge when developing next generation architectures for automated driving ECUs is to guarantee reliable functionality. Today’s fail safe systems will not be able to handle electronic failures due to the missing “mechanical” fallback or the intervening driver. This means, fail operational based on redundancy is an essential part for improving the functional safety, especially in safety-related braking and steering systems. The 2-out-of-2 Diagnostic Fail Safe (2oo2DFS) system is a promising approach to realize redundancy with manageable costs. In this contribution, we evaluate the reliability of this concept for a symmetric and an asymmetric Electronic Power Steering (EPS) ECU. For this, we use a Markov chain model as a typical method for analyzing the reliability and Mean Time To Failure (MTTF) in majority redundancy approaches. As a basis, the failure rates of the used components and the microcontroller are considered.

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.

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.

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 order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

During the charging Electric Vehicle (EV), power transfer occurs in the power electronics of an EV powertrain. Understanding how the Wireless Power Transfer (WPT) occurs would be beneficial for achieving convenient charging method. This paper focuses on improving WPT system pad compatibility, power transfer efficiency, EMI reduction, and Foreign Object Detection (FOD). The choice of convertible WPT pad for circular and DD type coil, improvement of pad compatibility is analyzed in this paper. In addition, several control methods of increasing WPT system efficiency are proposed. Firstly, the effect of Full Bridge - Half Bridge (FB-HB) is introduced, and the influence of a Bridgeless control scheme is discussed. A new, ferrite pad structure is applied to WPT system in order to achieve EMI reduction. Lastly, a new strategy of Foreign Object Detection (FOD) is suggested for WPT system using phase difference and frequency variation detection.

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.