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Model-based methodologies for the engine calibration process, employing engine cycle simulation and polynomial regression analysis, have been developed and the reliability of the proposed method was confirmed by validating the model predictions with dynamometer test data. From the results, it was clear that the predictions by the engine cycle simulation with a knock model, which considers the two-stage hydrocarbon ignition characteristics of gasoline, were in good agreement with the dynamometer test data if the model tuning parameters were strictly adjusted. Physical model tuning and validation were done, followed by the creation of a dataset for the regression analysis of charging efficiency, EGR mass, and MBT using a 4th order polynomial equation. The stepwise method was demonstrated to yield a logarithm likelihood ratio and its false probability at each term in the polynomial equation.

A new diagnosis method for an air-fuel ratio cylinder imbalance has been developed. The developed diagnosis method is composed of two parts. The first part detects an occurrence of an air-fuel ratio cylinder imbalance by using a two revolution frequency component of an EGO sensor output signal or an UEGO sensor output signal upstream from a catalyst. The two revolution frequency component is from a cycle where an engine rotates twice. The second part of the diagnosis method detects an increase of emissions by using a low frequency component which is calculated from the output of an EGO sensor downstream from the catalyst. When the two revolution frequency component calculated using the upstream sensor output is larger than a certain level and the low frequency component calculated using the downstream sensor output is shifted to a leaner range, the diagnosis judges that the emissions increase is due to an air-fuel ratio cylinder imbalance.

Highly automated driving systems have a responsibility to keep a vehicle safe even in abnormal conditions such as random or systematic failures. However, creating redundancy in a system to respond to failures increases the cost of the system, and simple redundancy cannot detect systematic failures because some systematic failures occur in each system at the same time. Systematic failures in automated driving systems cannot be verified sufficiently during the development phase due to numerous patterns of parameters input from outside the system. A safety concept based on a “safety sustainer” for highly automated driving systems is proposed. The safety sustainer is designed for keeping a vehicle in a safe state for several seconds if a failure occurs in the system and notifying the driver that the system is in failure mode and requesting the driver to take over control of the vehicle.

This paper presents a single-chip 32bit RISC microcontroller boarding on MY1998 dedicated to highly complicated powertrain management. The high performance 32bit RISC CPU provides the only solution to meet requirements of drastic CPU performance enhancement and integration. Furthermore, a 32bit counter, based on a 20 MHz clock, and a 32bit multiplier make possible misfire detection and precise analysis of the engine management strategy, especially cylinder individual air-fuel ratio control.

This paper describes a state adaptive control method for vehicle suspensions proposed by Hitachi, Ltd. The objective of the control is to improve riding comfort and driving stability in reaction to road iregularities, exterior wind forces, and changes in vehicle loads as well as in reaction to inertial changes during cornering, breaking, and accelerating. The objective is attained by making considerable use of the relative displacement data between the body and the suspension. The state adaptive control system includes four shock absorbers whose damping forces can be tuned in three stages, four height sensors which measure the relative displacement, a vehicle speed sensor, and a microcomputer which decides the optimal damper stage. The validity of the proposed control method is shown through computer simulations and actual driving experiments. Vertical acceleration is reduced by about 55 % by switching from the soft damper to the hard damper in a computer simulation.

A continuously variable valve event and lift (VEL) system, actuated by oscillating cams, can provide optimum lift and event angles matching the engine operating conditions, thereby improving fuel economy, exhaust emission performance and power output. The VEL system allows small lift and event angles even in the engine operating region where the required intake air volume is small and the influence of valvetrain friction is substantial, such as during idling. Therefore, the system can reduce friction to lower levels than conventional valvetrains, which works to improve fuel economy. On the other hand, a distinct feature of oscillating cams is that their sliding velocity is zero at the time of peak lift, which differs from the behavior of conventional rotating cams. For that reason, it is assumed that the friction and lubrication characteristics of oscillating cams may differ from those of conventional cams.

A new variable valve event and lift (VVEL) system has been developed by applying a multiple-link mechanism. This VVEL system can continuously vary the valve event angle and lift over a wide range from an exceptional small event angle and small lift and to a large event angle and large lift. This capability offers the potential to improve fuel economy, power output, emissions and other parameters of engine performance. The valve lift characteristics obtained with the VVEL system consist of a synthesis of the oscillatory motion characteristics of the multiple-link mechanism and the oscillating cam profile. With the multiple-link mechanism, the angular velocity of the oscillating cams varies during valve lift, but the valve lift characteristics incorporate both gentle ramp sections and sharp lift sections, the same as a conventional engine.

A totally integrated vehicle electronic control system is described, which optimizes vehicle performance through use of electronics. The system implements efficient coordination of functions of the engine, drive-train, brakes, steering, and suspension control subsystems to give a smoother ride, better handling and greater safety. The principles of the system are based on control and stability augmentation strategies. Each subsystem has two observers which control the force of the actuators according to the vehicle dynamics. The system features a driver support system which allows the average driver to employ the full performance potential of the vehicle in exceptional situations, and an artificial response control system to ensure optimum response and comfort. Application of the system allows the driver to experience a new level of performance and a marked improvement in handling quality and ride comfort.

A virtual power window control system was built in order to look into and demonstrate applications of microcontroller models. A virtual ECU simulated microcontroller hardware operations. The microcontroller program, which was written in binary digital codes, was executed step-by-step as the virtual ECU simulation went on. Thus, production-ready codes of ECUs are of primary interest in this research. The mechanical system of the power window, the DC motor to lift the window glass, the H-bridge MOSFET drivers, and the current sensing circuit to detect window locking are also modeled. This means that the hardware system of the control system was precisely modeled in terms of mechanical and circuit components. By integrating these models into continuous and discrete co-simulation, the power window control system was analyzed in detail from the microscopic command execution of the microcontroller to the macroscopic motion of the window mechanism altogether.

Generalized models of the air/fuel ratio control using estimated air mass in the cylinder were presented to obtain highly accurate control during transient conditions in high supercharged direct injection systems with a complex air induction system. The air mass change was estimated by using upstream models which estimated the pressure of the intake manifold by introducing the output of the air flow meter and the differential of the output into aerodynamic equations of the intake system. The air mass into the cylinders was estimated at the beginning of the intake stroke under a wide range of driving conditions, without compensating for changes in the downstream parameters of the intake system and engine. Therefore, the upstream models required relatively minor calibration changes for each engine modification to be able to estimate the air mass on a cylinder-by-cylinder basis.

In recent years, integrated vehicle control systems have been developed to improve fuel economy and safety. As a result, engine control is shifting to torque-based systems for throttle / fuel / ignition control, to realize an engine torque demand from the system. This paper describes torque-based engine control technologies for SI (Spark Ignition) engine to improve torque control accuracy using a feedback control algorithm and an airflow sensor.

An automatic matching method for engine control parameters is described which can aid efficient development of new engine control systems. In a spark-ignition engine, fuel is fed to a cylinder in proportion to the air mass induced in the cylinder. Air flow meter characteristics and fuel injector characteristics govern fuel control. The control parameters in the electronic controller should be tuned to the physical characteristics of the air flow meter and the fuel injectors during driving. Conventional development of the engine control system requires a lot of experiments for control parameter matching. The new matching method utilizes the deviation of feedback coefficients for stoichiometric combustion. The feedback coefficient reflects errors in control parameters of the air flow meter and fuel injectors. The relationship between the feedback coefficients and control parameters has been derived to provide a way to tune control parameters to their physical characteristics.

To detect difficult-to-find defects in automotive control systems, we have proposed a modeling method with a program slicing technique. In this method, a verifier adjusts the boundaries of source code to be extracted on a variable dependence graph, in a kind of data flow. We have developed software tools for this method and achieved a 35% decrease in total verification time on model checking. This paper provides some consideration on effective cases of the method from verification practices. There are two types of malfunction causes: one is the timing of processes (race conditions), and the other is complex logics. Each type requires different elements in external environment models. Furthermore, we propose regression verification based on the modeling method above, to further reduce verification time on model checking. The paper outlines tool extensions needed to realize regression verification.

In-vehicle networks are generally used for computerized control and connecting information technology devices in cars. However, increasing connectivity also increases security risks. “Spoofing attacks”, in which an adversary infiltrates the controller area network (CAN) with malicious data and makes the car behave abnormally, have been reported. Therefore, countermeasures against this type of attack are needed. Modifying legacy electronic control units (ECUs) will affect development costs and reliability because in-vehicle networks have already been developed for most vehicles. Current countermeasures, such as authentication, require modification of legacy ECUs. On the other hand, anomaly detection methods may result in misdetection due to the difficulty in setting an appropriate threshold. Evaluating a reception cycle of data can be used to simply detect spoofing attacks. However, this may result in false detection due to fluctuation in the data reception cycle in the CAN.

In order to develop a high-performance turbocharger turbine, compressible turbulent flow analysis is applied to the complicated flow around the nozzle vanes and the spacers. The flow analysis indicates that a combination of a curved nozzle vane and a round spacer causes a low-velocity region at the inner side of the nozzle vane even when the turbine efficiency is highest. As a result of the loss analysis, a teardrop-shaped spacer, which suppresses the low-velocity region and flow separation, is developed, and shown to improve the turbine efficiency. The easiness of the nozzle vane control is also important as well as the high efficiency. The fluid force on the nozzle vane depends on the flow pattern; therefore, the torque about the pivot of the nozzle vane is also numerically calculated.

The increasing number of controllable parameters in modern engine systems has led to increasingly complicated and enlarged engine control software. This in turn has created dramatic increases in software development time and cost. Model-based control design seems to be an effective way to reduce development time and costs and also to enable engineers to understand the complex relationship between the many controllable parameters and engine performance. In the present study, we have developed model-based methodologies for the engine calibration process, employing engine cycle simulation and regression analysis. The reliability of the proposed method was investigated by validating the regression model predictions with measured data.

The concept of a “controller grid”, which makes effective use of computational resources distributed on a network while guaranteeing real-time operation, is proposed and applied to realize highly advanced control. It facilitates the total optimization of a plant control and achieves the high efficiency that is not acquired by individual plant optimization. To realize this concept, migration of a control task customized to be executed on one particular microcontroller to another microcontroller is necessary while strictly observing the required response time. Two techniques to meet this requirement are proposed: “task migration” for a control system and “real-time guaranteed scheduling of task migration and execution”. The effectiveness of the controller grid is assessed by applying it in experiments with electronic-throttle-body (ETB) advanced control.

The problem of high fatal accident rates due to drunk driving persists, and must be reduced. This paper reports on a prototype system mounted on a car mock-up and a prototype portable system that enables the checking of the drivers’ sobriety using a breath-alcohol sensor. The sensor unit consists of a water-vapor-sensor and three semiconductor gas sensors for ethanol, acetaldehyde, and hydrogen. One of the systems’ features is that they can detect water vapor from human-exhaled breath to prevent false detection with fake gases. Each gas concentration was calculated by applying an algorithm based on a differential evolution method. To quickly detect the water vapor in exhaled breath, we applied an AC voltage between the two electrodes of the breath-water-vapor sensor and used our alcohol-detection algorithm. The ethanol level was automatically calculated from the three gas sensors as soon as the water vapor was detected.

We propose low inductance batteries and enhance power density for a inverter. Conventionally, the capacitors are used for smoothing ripple of the inverter. The low inductance battery which responds at carrier frequency of inverter can reduce the capacity of the smoothing capacitors and enable to enhance power density for the inverter. For reducing the inductance, it is necessary to separately understand the impact of electrochemical reaction under wide range of assumed conditions and structural reaction on frequency characteristics. Furthermore, it is also necessary to design the low inductance batteries based on combining the both of characteristics. However, there are no study focusing on modeling by combining such different domains. Therefore, we made original inductance model inside battery considering frequency characteristics among all materials and structural influence with electromagnetic field analysis simulator.

In recent years, improvement of in-use fuel economy is required with tightening of exhaust emission regulation. We assume that one of the most effective solutions is ACC (Adaptive Cruise Control), which can control a powertrain accurately more than a driver. We have been developing a fuel saving ADAS (Advanced Driver Assistance System) application named “Sailing-ACC”. Sailing-ACC system uses sailing stop technology which stops engine fuel injection, and disengages a clutch coupling a transmission when a vehicle does not need acceleration torque. This system has a potential to greatly improve fuel efficiency. In this paper, we present a predictive powertrain state switching algorithm using external information (route information, preceding vehicle information). This algorithm calculates appropriate switching timing between a sailing stop mode and an acceleration mode to generate a “pulse-and-glide” pattern.