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In real-world automotive control, there are many constraints to be considered. In order to explicitly treat the constraints, we introduce a model-prediction-based algorithm called a reference governor (RG). The RG generates modified references so that predicted future variables in a closed-loop system satisfy their constraints. One merit of introducing the RG is that effort required in control development and calibration would be reduced. In the preceding research work by Nakada et al., only a single reference case was considered. However, it is difficult to extend the previous work to more complicated systems with multiple references such as the air path control of a diesel engine due to interference between the boosting and exhaust gas recirculation (EGR) systems. Moreover, in the air path control, multiple constraints need to be considered to ensure hardware limits. Hence, it is quite beneficial to cultivate RG methodologies to deal with multiple references and constraints.

Conventional CFD-based shape optimization technology that uses parametric shape modification and optimal solutions searching algorithms has the two problems: (1) outcome of optimized shapes depend on the selection of design parameters made by the designer, and (2) high computational costs. To resolve those problems, two innovative inverse analysis technologies based on the Adjoint Method were developed in previous study: surface geometry deformation sensitivity analysis to identify the locations to be modified, and topology optimization to generate an optimal shape for maximizing the cost function in the constrained design space. However, these technologies are only applicable to steady flows. Since most flows in a vehicle (such as engine in-cylinder flow) are transient, a practical technology for surface geometry sensitivity analysis has been developed based on the Transient Adjoint Method.

Many vehicles are currently equipped with active safety systems that can detect vulnerable road users like pedestrians and bicyclists, to mitigate associated conflicts with vehicles. With the advancements in technologies and algorithms, detailed motions of these targets, especially the limb motions, are being considered for improving the efficiency and reliability of object detection. Thus, it becomes important to understand these limb motions to support the design and evaluation of many vehicular safety systems. However in current literature, there is no agreement being reached on whether or not and how often these limbs move, especially at the most critical moments for potential crashes. In this study, a total of 832 pedestrian walking or cyclist biking cases were randomly selected from one large-scale naturalistic driving database containing 480,000 video segments with a total size of 94TB, and then the 832 video clips were analyzed focusing on their limb motions.

High frequency wind noise caused by turbulent flow around the front pillars of a vehicle is an important factor for customer perception of ride comfort. In order to reduce undesirable interior wind noise during vehicle development process, a calculation and visualization method for exterior wind noise with an acceptable computational cost and adequate accuracy is required. In this paper an index for prediction of the strength of exterior wind noise, referred to as Exterior Noise Power (ENP), is developed based on an assumption that the acoustic power of exterior wind noise can be approximated by the far field acoustic power radiated from vehicle surface. Using the well-known Curle’s equation, ENP can be represented as a surface integral of an acoustic intensity distribution, referred to as Exterior Noise Power Distribution (ENPD). ENPD is estimated from turbulent surface pressure fluctuation and mean convective velocity in the vicinity of the vehicle surface.

When vehicles run on the flooded road, water enters to the engine compartment and sometimes reaches the position of the air intake duct and electrical parts and causes the reliability problems. Numerical simulation is an effective tool for this phenomenon because it can not only evaluate the water level before experiment but also identify the intrusion route. Recently, the gap around the engine cooling modules tends to become smaller and the undercover tends to become bigger than before in order to enhance the vehicle performance (e.g., aerodynamics, exterior noise). Leakage tightness around the engine compartment becomes higher and causes an increase of the buoyancy force from the water. Therefore the vehicle attitude change is causing a greater impact on the water level. This paper describes the development of a water level prediction method in engine compartment while running on the flooded road by using the coupled multibody and fluid dynamics.

This paper presents a modeling method for prediction of low-frequency road noise in a steady-state condition where rotating tires are excited by actual road profile undulation input. The proposed finite element (FE) tire model contains not only additional geometric stiffness related to inflation pressure and axle load but also Coriolis force and centrifugal force effects caused by tire rotation for precise road noise simulation. Road inputs act on the nodes of each rib in the contact patch of the stationary tire model and move along them at the driving velocity. The nodes are enforced to displace in frequency domain based on the measured road profile. Tire model accuracy was confirmed by the spindle forces on the rotating chassis drum up to 100Hz where Coriolis force effect should be considered. Full vehicle simulation results showed good agreement with the vibration measurement of front/rear suspension at two driving velocities.

In this paper, the authors introduce the spark plug for misfire detection system by ion current. In order to realize high accuracy misfire detection, the signal of ion current must be larger than that of noise. For maintaining ion signal in all designed lifetime, the configuration and initial condition of spark position are derived by an experiment and consideration about degradation in use. Additionally, the cause of noise is determined by an observation and a theoretical study, and we indicate the method to inhibit noise efficiently. Finally, effect of the methods found by these two approaches is confirmed with an engine, and we propose specifications of spark plug satisfying the condition that realize high accuracy detection by ion current.

This paper considers an application of reference governor (RG) to automotive diesel aftertreatment temperature control. Recently, regulations on vehicle emissions have become more stringent, and engine hardware and software are expected to be more complicated. It is getting more difficult to guarantee constraints in control systems as well as good control performance. Among model-based control methods that can directly treat constraints, this paper focuses on the RG, which has recently attracted a lot of attention as one method of model prediction-based control. In the RG, references in tracking control are modified based on future prediction so that the predicted outputs in a closed-loop system satisfy the constraints. This paper proposes an online RG algorithm, taking account of the real-time implementation on engine embedded controllers.

For a luxury sedan, quietness is a major selling point, and a hybrid luxury sedan is expected to be especially quiet. Therefore, in the development of the hybrid luxury sedan, every possible effort is needed to reduce the hybrid system noise in order to ensure a level of quietness far superior to that of an ordinary gasoline-powered vehicle. In addition, the noise and vibration phenomena that are particular to vehicles with longitudinal power trains require special reduction technologies. This paper first describes the superior quietness of hybrid luxury vehicles in comparison with ordinary gasoline-powered vehicles. This paper then addresses the development issues of vibration during engine starting, engine booming noise, and motor noise, explaining the mechanisms by which they are generated and the technologies employed to reduce them.

It is difficult to improve tire cavity noise since the pressure of cavity resonance acts as a compelling force, and its low damping and high gain characteristics dominate the vibration of both the suspension and body. For this reason, the analysis described in this article aimed to clarify the design factors involved and to improve this phenomenon at the source. This was accomplished by investigating the acoustic coupling vibration mode of the wheel, which is the component that transmits the pressure of cavity resonance at first. In addition, the vibration characteristic of suspension was investigated also. A speaker-equipped sound pressure generator inside the tire and wheel assembly was developed and used to infer that wheel vibration under cavity resonance is a forced vibration mode with respect to the cavity resonance pressure distribution, not an eigenvalue mode, and this phenomenon may therefore be improved by optimizing the out-of-plane torsional stiffness of the disk.

Whinning gear noise(final gear noise), one of the causes for automobile interior noise is due to the exciting force of final gear kit and as a general countermeasure for this problem, a reduction of resonance level in transfer system and better meshing of gears have been utilized. However,vibration characteristics of final gear unit have not been considered much in this case. Authors have executed impacting test on final gear unit and confirmed its vibration characteristics. Based on this fact,vibration model consisting of bearings and gears spring system was constructed to evaluate vibration characteristics of final gear unit along with the results obtained from final gear unit of front engine,rear drive passenger car.

An obstacle recognition algorithm for the Pre-Crash Safety system has been newly developed with a stereo vision system and a millimeter wave radar with additional functions. This algorithm uses the merits of both the millimeter wave radar and the stereo vision system, and has two main features. One feature utilizes the merits of the stereo vision system detection with the detection results from the millimeter wave radar allowing for a more detailed horizontal position and width of the obstacle. This enables the equipment to operate at an earlier stage according to how well the relationship between the vehicle and the obstacle is understood. Another feature fuses detection from the millimeter wave radar and the stereo vision system. This system has succeeded in enhancing the detection performance of pedestrians who have been more difficult to detect than reflective objects such as cars.

Toyota Motor Corporation has already designed and developed vehicle brake control systems for relatively low speed off-road driving, such as Downhill Assist Control, Hill-start Assist Control and Active Traction Control. Though off-road utility is improved by virtue of these systems, in specific situations actual performance still depends on driving technique since the driver is required to control the accelerator pedal. Toyota has integrated these existing systems, and developed a new driving technology for off-road driving called “Crawl Control.” Crawl Control automatically modulates brake torque and drive torque to help keep the vehicle speed constant and slow. Unskilled drivers can thereby attain improved capabilities in places where high-level driving techniques are required. This system also reduces the effort required to control the accelerator and the brake pedal. This paper presents a new control algorithm for the realization of this Crawl Control system.

Merging a CAE shape optimization system and a concept Taguchi method SN-ratio index, a robustness-focused automated shape optimization method has been developed. Applying this method to diesel intake ports, with mold position tolerance set as the error factor, SN-ratio was defined for swirl stability. As a result of the optimization provided by a multi-objective genetic algorithm, simultaneous improvement of flux, swirl rotation and SN ratio was achieved.

Continuously variable transmission (CVT) and hybrid systems, which have metal belts and electrical units not found in conventional transmissions, are susceptible to extremely High Frequency belt and electromagnetic noise between 5 to 10 kHz. The evaluation and reduction of high frequency (HF) noise of 5 kHz and more is therefore a critical point for improving the quietness of vehicles installed with such systems. This article describes new sound source search technology capable of identifying sources of noise up to 15 kHz in the vehicle interior. Unlike conventional beamforming methods, this new system uses an improved microphone array provided with additional acoustic material. This article outlines the development of the system and its application to sound source identification of HF noise in a hybrid vehicle.

In this study, a new practical design method (tool) for engine sound quality in a car interior is proposed. The tool can automatically create the target interior sound using the psychoacoustic index ‘powerfulness’ based on subjective tests. Moreover, it can calculate the intake noise characteristic to create the target interior sound and select the suitable intake specification from the prepared database. By using this method sound engineering can be easily and effectively carried out without manufacturing an experimental car.

The world's first mass production gasoline hybrid passenger car, the “Prius”, was introduced into the Japanese market in 1997. By the time it was introduced into the American and European markets in Mid-2000, its fuel consumption and exhaust emissions had been further improved while achieving superior NV performance compared with conventional vehicles with 1.5-liter engines even in these competitive markets. This paper describes NV reduction technology for problems peculiar to the hybrid vehicle such as engine start/stop vibration, drone noise and vibration at low engine speed and motor/generator noise and vibration. It also compares the overall NV performance of the hybrid vehicle with conventional gasoline engine vehicles.

This paper describes and discusses the result of a comprehensive simulation analysis we have carried out to clarify the effects of gear dimensions, tooth surface modification, and manufacturing error on the static transmission error of automotive hypoid gears. Three representative factors have been analyzed contact ratio, crowning and pitch error because these characteristics play the most important role in tooth dimensions, tooth surface modification and manufacturing error. The analysis has clarified the effect of each factor on gear noise, making it possible to prepare a guideline for optimal design of gear dimensions and tooth surface modification under various conditions.

Statistical Energy Analysis (SEA) is a promising tool for developing an efficient sound package design for reducing airborne interior noise at high frequencies. The optimal sound package, however, is not directly predicted by using the SEA vehicle model alone and therefore requires parametric studies of sound package configurations. This paper describes an effective method for using SEA modeling to achieve the desired interior noise level targets. A mathematical model, expressed by one equation, is derived on the assumption that the directions of the power flows are known in the SEA model. This equation describes the relationship between sound package properties and the resulting interior noise level. Using the relationship between weight and performance of sound package, an efficient configuration can be determined. The predicted sound pressure level of the vehicle interior with the optimized sound package correlated well to the experimental data for the case presented in this paper.

The renewed platform of the upcoming flagship front-engine, rear-wheel drive (FR) vehicles demands high levels of driving performance, fuel efficiency and noise-vibration performance. The newly developed driveline system must balance these conflicting performance attributes by adopting new technologies. This article focuses on several technologies that were needed in order to meet the demand for noise-vibration performance and fuel efficiency. For noise-vibration performance, this article will focus on propeller shaft low frequency noise (booming noise). This noise level is determined by the propeller shaft’s excitation force and the sensitivity of differential mounting system. In regards to the propeller shaft’s excitation force, the contribution of the axial excitation force was clarified. This excitation force was decreased by adopting a double offset joint (DOJ) as the propeller shaft’s second joint and low stiffness rubber couplings as the first and third joints.