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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.

Human drivers navigate by continuously predicting the intent of road users and interacting with them. For safe autonomous driving, research about predicting future trajectory of vehicles and motion planning based on these predictions has drawn attention in recent years. Most of these studies, however, did not take into account driver’s intentions or any interdependence with other vehicles. In order to drive safely in real complex driving situations, it is essential to plan a path based on other driver’s intentions and simultaneously to estimate the intentions of other road user with different characteristics as human drivers do. We aim to tackle the above challenges on highway merge scenario where the intention of other road users should be understood. In this study, we propose an intention aware motion planning method using finite state machine and model predictive control without any vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communications.

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.

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.

It has become an important trend to implement safety-related requirements in the road vehicles. Recent studies have shown that accidents, which occurred when drivers are not focused due to fatigue or distractions, can be predicted in advance when using safety features. Advanced Driver Assistance Systems (ADAS) are used to prevent this kind of situation. Currently, many major tiers are using a DSP chip for ADAS applications. This paper suggests the migration from a DSP configuration to a Microcontroller configuration for ADAS application, for example, using a 32bit Multi-core Microcontroller. In this paper, the following topics will be discussed. Firstly, this paper proposes and describes the system block diagram for ADAS configuration followed by the requirements of the ADAS system. Secondly, the paper discusses the current solutions using a DSP. Thirdly, the paper presents a system that is migrated to a Multi-core microcontroller.

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 describes the effects of diverse driving modes and vehicle component characteristics impact on fuel efficiency and emissions of light commercial vehicles. The AVL's vehicle and powertrain system level simulation tool (CRUISE) was adopted in this study. The main input data such as the fuel consumption & emission map were based on the experimental value and vehicle components characteristic data (full load characteristic curves, gear shifting position curves, torque conversion curve etc.) and basic specifications (gross weight, gear ratio, tire radius etc.) were used based on the database or suggested value. The test database for two diesel vehicles adopted whether prediction accuracy of simulation data were converged in acceptable range. These data had been acquired from the portable emission measurement system, the exhaust emission and operating conditions (engine speed, vehicle speed, pedal position etc.) were acquired at each time step.

This paper describes the effect of DME-LPG blended fuels on the macroscopic spray characteristics in a high pressure diesel injection system. In this work, the DME-LPG blended fuel that 30% LPG (butane) was blended into pure DME by weight ratio. In order to investigate the macroscopic spray characteristics such as spray tip penetration, spray cone angle, and spray area were measured under the various injection parameters. The experimental results were compared the blended fuels with pure DME. In the experiment, a single-hole nozzle injector with nozzle hole diameter of 0.3mm was used to investigate the macroscopic spray behavior characteristics of DME-LPG blended fuel. The experimental results of DME-LPG blended fuels showed that spray tip penetration was increased according to increasing injection pressure. The spray tip penetration and the spray area of DME-LPG blended fuel was slightly shorter than that of DME, and the both fuels showed similar trends of spray angle.

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.

In present days, most of researches concerned with vehicle engines have been performed to reduce vehicle emissions and to improve engine efficiency. For the requirements, LPG (Liquefied Petroleum Gas) engine which has lots of advantages such as low emission level, cheaper fuel cost and enough infrastructures has had lots of interest as an alternative fuel engine. What is more, it has a low emission level of CO2 well-known as the factor of ‘Global Warming’, thus the use of LPG engines has been increased. Especially since MPI(Multi Point Injection) type LPLi(Liquid Phase LPG injection) system was used for the fuel supply system, disadvantages of LPG engine such as low engine performance, decreased charging efficiency and cold starting difficulty have been improved and prejudices against LPG engines have been changed a lot. In light of this, the motion to use LPLi engines instead of diesel engines has been increasing.

Automotive manufacturers and engineers have paid attention to promoting engine performance with low emissions satisfying many emission regulations. With such goals in mind, we have investigated new cooling strategies such as high coolant temperature control, fast warm-up and post cooling using an automotive cooling system controlled by electronic actuators. The cooling system in a 2.7 liter HSDI engine was modified for the purpose of this study, and an engine experiment was carried out on a New European Drive Cycle (NEDC). The conventional water pump was decoupled from the engine and electronically controlled by a BLDC motor. Valves were installed at the coolant pathways between the engine and cooling components. Overall, this modification led to a reduction in both fuel consumption and exhaust gas emissions (e.g. THC, CO). The reduction was particularly considerable at the low speed and low load-drive conditions by controlling high temperature of the coolant.

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.

A control method using an in-cylinder pressure sensor can directly and precisely control engine combustion, lowering harmful emissions and fuel consumption levels. However, this method cannot be applied to a conventional engine management system because of its inaccuracy and the high cost of the pressure sensor, as well as the high computational load. In this study, we propose a real-time IMEP estimation method for a common rail direct injection diesel engine using the difference pressure integral as a cylinder pressure variable. The proposed method requires less computational load, enabling the IMEP to be estimated in real-time. In addition, we validated the estimation algorithm through simulation and engine experiments. The IMEP was accurately estimated with a small root mean square error of below 0.2305 bar.

As the exhaustion of petroleum resources and air pollution problems are getting more serious day by day, demands for low emission levels and higher thermal efficiency of vehicle engines have been increased. In light of this, the diesel engine has many advantages such as high thermal efficiency, a cheaper price of fuel, and what is more it has a low CO2 exhaustion level well known as the factor of ‘Global Warming’, therefore the use of diesel engines is getting increased. However in the case of diesel engine, NOx increases in the local high temperature region, and particulate matter increases in fuel rich regions. That is why, getting down the peak temperature to reduce NOx emission and making better air-fuel mixing to minimize particulate matter formation are required and Homogeneous Charge Compression Ignition (HCCI) is a technique which can make those conditions.

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.

Electro-hydraulic brake (EHB) provides improved braking and stability functions such as ABS, TCS, ESC, EBD, etc. It also removes complex mechanical parts for freedom of design, improves maintenance requirements and reduces unit weight. But, the EHB should be at least as reliable as the conventional hydraulic brake system. In this paper, the model-based fault diagnosis system is developed to monitor the brake status using the analytical redundancy method. The performance of the model-based fault diagnosis system is verified in simulations and demonstrates the effectiveness of the proposed system in various faulty cases.

Electromechanical relays that are coupled with fuses have been used for controlling electrical loads in vehicles. In the past decade, semiconductor power switches have been developed for overcoming the physical limits of relays and fuses. Semiconductor power switches can not only replace relays and fuses but can also improve a system's reliability and efficiency. In this study, we introduce the Smart Automotive Switch (SAS), which is a smart high side power switch of Fairchild Korea semiconductor. Functional capabilities, such as power switching, protection and self-diagnosis of SASs are presented in case studies involving, for example, headlights, glow plugs, and fuel pump control systems. Through these experimental studies, the suitability of SASs is validated for designing improved automotive electronic control systems.

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.

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.