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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 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.

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.

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.

This paper presents the Matlab/Simulink-based Software-in-the-Loop Simulation (SILS) tool which is the co-simulator for temporal and functional simulations of control systems. The temporal behavior of a control system is mainly dependent on the implemented software and hardware such as the real-time operating system, target CPU and communication protocol. In this research, the SILS components with temporal attributes are specified as tasks, task executions, real-time schedulers, and real-time networks. Methods for realizing these components in graphical block representations are investigated with Matlab/Simulink, which is the most commonly used tool for designing and simulating control algorithms in control engineering. These components are modeled in graphical blocks of Matlab/Simulink.

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.

This paper presents a preliminary study of a sampling period decision for robust control of a distributed control system based on an in-vehicle network with three types of data (real-time synchronous data, real-time asynchronous data, and nonreal-time asynchronous data). The architecture of automotive systems is currently changing from a number of standalone electronic control units (ECUs) to a functionally integrated distributed system which is linked by a network. The control performance of the integrated networked control system can be changed by the characteristics of time delays among the application ECUs. A basic parameter for a scheduling method of the networked control systems, a maximum allowable delay bound is used, which guarantees stability of the networked control system, and it is derived from the characteristics of the given plant using presented theorems.

Since many electric and electronic systems are continuously added in a vehicle to meet various regulations and customer demands over the last decade, the demand on the electric power have been substantially increased. Furthermore the idle time fraction during the vehicle traveling has been increased due to the heavy urban traffic condition. The electric power system of the modern vehicle has to supply enough electrical energy to numerous electrical and electronic systems. A detailed understanding of the characteristics of the electric power system, electrical load demands, and driving environment such as road, season, and vehicle weight are required when the capacities of generator and battery are determined for a vehicle. In order to avoid an over or under design problem of the electric power system, a simulation program for electric power estimation is adequate.

The electrical power system is the vital lifeline to most of the control systems on modern vehicles. The demands on the system are highly complex, and a detailed understanding of the system behavior is necessary both to the process of systems integration and to the economic design of a specific control system or actuator. The vehicle electric power system, which consists of two major components: a generator and a battery, has to provide numerous electrical and electronic systems with enough electrical energy. 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. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study.

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.