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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 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.

In order to satisfy increasing customer demands on ride quality as well as expectations for off-road performance of sport-utility vehicles (SUVs), it is necessary to develop technologies which offer enhanced levels of both performances. For ride quality, it is important to minimize body roll angle during cornering, which is achieved by suppressing suspension travel, and also to reduce vertical motion during straight-ahead travel. While for off-road performance, it is necessary to allow a long suspension stroke to allow a high level of off-road traction by delivering driving force reliably to the surface. These two performance parameters require a tradeoff with respect to vehicle roll stiffness. To reconcile these conflicting performance requirements, for first time in the world we adopted for production vehicles the system which connects the four shock absorbers together.

We developed a thermal calculation 1D simulator for an electric valve timing control system (VTC). A VTC can optimize the open and close timing of the intake and exhaust valves depending on the driving situation. Since a conventional VTC is driven hydraulically, the challenges are response speed and operation limit at low temperature. Our company has been developing an electric VTC for quick response and expansion of operating conditions. Currently, it is necessary to optimize the motor and reduction gear design to balance quicker response with downsizing. Therefore, a coupled simulator that can calculate electricity, mechanics, control, and thermo characteristics is required. In 1D simulation, a thermal network method is commonly used for thermal calculation. However, an electric VTC is attached to the end of a camshaft; therefore, determining thermal resistances is difficult. We propose a method of determining thermal resistances, using both theoretical and experimental approaches.

This paper presents the “Virtual Failure Mode and Effects Analysis (vFMEA)” system, which is a high-fidelity electrical-failure-simulation platform, and applies it to the software verification of an electric power steering (EPS) system. The vFMEA system enables engineers to dynamically inject a drift fault into a circuit model of the electronic control unit (ECU) of an EPS system, to analyze system-level failure effects, and to verify software-implemented safety mechanisms, which consequently reduces both cost and time of development. The vFMEA system can verify test cases that cannot be verified using an actual ECU and can improve test coverage as well. It consists of a cycle-accurate microcontroller model with mass-production software implemented in binary format, analog and digital circuit models, mechanical models, and a state-triggered fault-injection mechanism.