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We developed a flexible system with EVs for solving imbalance between electricity demand and supply avoiding degradation of EV’s battery life. Such flexible systems are commonly being examined but nothing the system which uses battery considering impact of its battery life to avoid shorten EV’s operation period. Therefore, we developed one of methodologies to select preferable load facilities based on imbalance trend and flexible prices. The imbalance trend means a duration of the imbalance. The flexible prices mean operation cost to provide flexibility. By comparing the flexible prices and operation profit, it is possible to prevent unnecessary operation. As a result, we demonstrated our flexible system works as designed based on these parameters.

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.

Suspension is an important chassis part which is vital to ride comfort [1]. However, it is difficult to achieve our targeted comfortability level in a short time. Therefore, improving efficiency of damper development is our primary challenge. We have launched a project which aims to reduce the workload on developing dampers by introducing analytical approaches to the improvement of ride comfort. To be more specific, we have been putting effort into developing the damping force prediction, the vehicle dynamics prediction and subjective rating prediction. This paper describes subjective rating prediction method which output a subjective rating corresponding to the physical value of the vehicle dynamics with deep learning. As a result of verification using objective data which was not used for learning process, DNN (Deep Neural Network) prediction method could fairly precisely predict subjective rating of the expert driver.

We propose a combined battery system (CBS) for low cost electric vehicles (EVs) to enhance battery life. The EVs popularly called as Neighborhood Electric Vehicle or Low-Speed-Electric-Vehicle are spreading in developing countries. Conventionally the EVs batteries consist of high energy density cells, and we call it as energy cells (EC). A major issue with the EVs is high operational costs mainly due to high battery cost and short lifespan of the ECs. In this study, we develop a CBS consisting of a combination of following two kinds of batteries: i) EC which is the main energy source for the EV, and ii) a battery having high power density also called as power cells (PC) which is more suitable to bear high charge-discharge currents. The key feature of the proposed system is to minimize the size of additional battery by using our high power lithium ion battery. We performed experiments to estimate EC life for several capacity values of the PC.

We have developed a drive cycle (DC) to test Hitachi’s combined battery system (CBS) for electric vehicles (EVs) having battery lifespan enhancements. Conventionally EV batteries consist of high energy density cells, and we call them as energy cells (EC). A major issue with the EVs is high operational costs mainly due to short lifespan of the ECs. CBS almost doubles the EC and thus overall battery system lifespan, as per the evaluation over a WLTP based method. We want to test the CBS under Indian conditions which has predominantly hot weather, and traffic jam scenarios. Battery deterioration and thus its lifespan is sensitive to traffic conditions and ambient temperature. Hence, it was needed to evaluate the CBS over an Indian DC and use 40°C as ambient temperature. However, it was difficult to carry out the tests since there is no standard Indian DC for small / light weight four wheelers.

We have developed a cooperative simulation environment for multiple electronic control units (ECUs) including a parallel executions mechanism to improve the test efficiency of a system, which was designed with multiple ECUs for autonomous driving. And we have applied it to a power window system for multiple ECUs with a controller area network (CAN). The power window model consists of an electronic-mechanical model and a CPU model. Each simulator with a different executions speed operates in parallel using a synchronization mechanism that exchanges data outputted from each simulator at a constant cycle. A virtual ECU simulated microcontroller hardware operations and executed its control program step-by-step in binary code to test software for the product version. As co-simulation technology, a mechanism that synchronously executes heterogeneous simulators and a model of an in-vehicle communication CAN connecting each ECU were developed.

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.

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.

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.

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.

Safety concepts are essential to conform to functional safety standard ISO 26262 for automotive products. Safety requirements, which are a part of safety concepts, shall be satisfied by products to avoid hazards by vehicles to maintain their safety. Incompleteness of safety requirements must be avoided in deriving parent requirements to its children. However, measure for checking is only reviewing when the safety requirements are described in a natural language. This measure for checking is not objective or stringent. We developed a specification technique written in formal notation that addresses some of the shortcomings of capturing safety requirements for verification purposes. Safety requirements in this notation are expressed in goal tree models, which originate from goal-oriented requirement engineering Knowledge Acquisition in autOmated Specification (KAOS). Each requirement is written with propositional logic as the node of a tree.

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.

The ISO 26262 is a functional safety standard for road vehicles. The standard requires manufacturers to conduct quantitative assessment of the diagnostic coverage (DC) of products. The DC is defined as the percentage of failure probability covered by safety mechanisms. However, DC evaluation methods for drift faults, in which the change in element values is not constant, have not been discussed. In this paper, we propose a DC evaluation method for analog circuits with drift faults. With this method, we first parameterize the effect of drift faults onto a bounded region then split the region into safe fault, hazardous detectable fault, and hazardous undetectable fault regions. We evaluate the classification rate distribution by the area ratios of these regions.

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.

“Virtual Failure Mode and Effects Analysis” (vFMEA), a novel safety-verification method of control software for automotive electronic systems, was proposed to save prototyping cost at verification stage. The proposed vFMEA is system-level FMEA method, which uses virtualized electronic control units (ECUs) consisting of microcontroller models on a microcontroller simulator and a transistor-level circuit models on a circuit simulator. By using the structure, the control software in binary code formats can be verified when a circuit-level fault occurs in the ECU hardware. As an illustrative example, vFMEA was applied to an engine ECU. As a result of short-circuit fault into a driver IC, engine revolution and engine speed decreased. However, the engine continued to operate normally when an open-circuit fault occurred in a capacitor connected in parallel. Effects of the hardware faults in ECU on a vehicle are demonstrated; thereby software verification can be performed using vFMEA system.

We have developed a system for automatic deceleration upon entering curves to prevent collisions on tight curves on high-ways. The navigation system is used to determine safe speed negotiating the curve, defined as a speed that will keep lateral acceleration within a settled value. The navigation system sends the curve radius to a controller, which calculates the safe speed for the curve. The controller then sends the speed command to the ACC system, which adjusts the vehicle speed. One of the important features in this system is the estimation of the vehicle position, in terms of its distance from the curve entrance. Navigation systems have a certain amount of dispersion in positional accuracy. A front camera is used in our system to decrease this dispersion. This camera detects lane markers (white lines, raised pavement markers, etc.) using our line recognition technologies1).

This paper proposes a new development method for highly reliable real-time embedded control systems using a CPU model-based hardware/software co-simulation. We take an approach that allows the full simulation of the virtual mechanical control system including CPU and object code level software. In this paper, Renesas SH-2A microcontroller model was developed on CoMET™ platform from VaST Systems Technology. A ETC (Electronic Throttle Control) system and engine control system were chosen to prove this concept. The ETB (Electronic Throttle Body) model on Saber® simulator from Synopsys® or engine model on MATLAB®/Simulink® simulator from MathWorks can be simulated with the SH-2A model. To help the system design, debug and evaluation, we developed an integrated behavior analyzer, which can display CPU behavior graphically during the simulation without affecting the simulation result, such as task level CPU load, interrupt statistics, software variable transition chart, and so on.

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.

Every fuel injection system for DI gasoline engines has a DC-DC converter to provide high, stabile voltage for opening the injector valve more quickly. A current control circuit for holding the valve open is also needed, as well as a large-capacity capacitor for pilot injection. Since these components occupy considerable space, an injector drive unit separate from the ECU must be used. Thus, there has been a need for a fuel injection system that can inject a small volume of fuel without requiring high voltage. To meet that need, we have developed a dual coil injector and an opening coil current control system. An investigation was also made of all the factors related to the dynamic range of the injector, including static flow rate, fuel pressure, battery voltage and harness resistance. Both efforts have led to the adoption of a battery voltage-driven fuel injector.

Gasoline engine control continues to become more sophisticated and so the amount of software has reached 10 to 20 times that of early control systems. By changing the embedded microcomputer from 8bit CISC (Complex Instruction Set Computer) to 32bit RISC (Reduced Instruction Set Computer), processing performance has been improved 100 times. This paper evaluates quantitative performance of the RISC CPU having a FPU (Floating Point Processing Unit) and describes an example application to adaptive control.