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This paper presents a custom integrated circuit (IC) on which circuit functions necessary for “Active Hydraulic Brake (AHB) system” are integrated, and its key component, “Current-to-Digital Converter” for solenoid current measurement. The AHB system, which realizes a seamless brake feeling for Antilock Brake System (ABS) and Regenerative Brake Cooperative Control of Hybrid Vehicle, and the custom IC are installed in the 4th-generation Prius released in 2015. In the AHB system, as linear solenoid valves are used for hydraulic brake pressure control, high-resolution and high-speed sensing of solenoid current with ripple components due to pulse width modulation (PWM) is one of the key technologies. The proposed current-to-digital converter directly samples the drain-source voltage of the sensing DMOS (double-diffused MOSFET) with an analog-to-digital (A/D) converter (ADC) on the IC, and digitizes it.

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.

One way to improve the fuel efficiency of HVs is to reduce the losses and size of the Power Control Unit (PCU). To achieve this, it is important to reduce the losses of power devices (such as IGBTs and FWDs) used in the PCU since their losses account for about 20% of the total loss of an HV. Furthermore, another issue when reducing the size of power devices is ensuring the thermal feasibility of the downsized devices. To achieve the objectives of the 4th generation PCU, the following development targets were set for the IGBTs: reduce power losses by 19.8% and size by 30% compared to the 3rd generation. Power losses were reduced by the development of a new Super Body Layer (SBL) structure, which improved the trade-off relationship between switching and steady-state loss. This trade-off relationship was improved by optimizing the key SBL concentration parameter.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

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.

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.

An investigation was conducted into pressure pulsation in the exhaust port, which greatly affects volumetric efficiency and engine performance. From experiments using a single blow-down generator, it was established that the amplitude of the pressure pulsation increases as the manifold branch is lengthened and that large negative pressure synchronized with the timing of valve overlap can be obtained if a proper branch length is used. The performance of a 2ℓ test engine was optimized by varying the length of both the manifold branches and front pipe forks. It was found that whereas front pipe fork length affects engine performance over only a narrow range of engine speed, optimizing manifold branch length results in a considerable improvement over a wide engine speed range. In the course of optimizing the exhaust pipe manifold length of this two-degree-of-freedom exhaust system, abnormal exhaust noises were emitted at specific engine speeds during deceleration.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

This paper describes that a method has been developed to estimate the range of the scatter of Head Injury Criterion (HIC) values in pedestrian impact tests, which could help to reduce the range of the scatter of HIC values by applying the stochastic method for Finite Element (FE) analysis. A major advantage of this method is that it enables the range of scatter of HIC values to be estimated and to explain the mechanics of the behavior. The test procedure of pedestrian impact allows some tolerances for the resultant conditions of impact such that the distance of actual impact location from the selected point is within 10 mm and the impact velocity is within ±0.7 km/h [1]. A HIC value calculated by impact simulation under a deterministic impact condition with the nominal input data does not necessarily represent the variation of measured data in impactor tests.

Automobile manufacturers have increased the pace of vehicle development in recent years to respond to diverse market demands. Consequently, it has become crucial for manufacturers to develop new technology which enables a particular vehicle to simultaneously achieve both ride comfort and handling performance at an optimal level. This article introduces the suspension design technology applying the Principal Elastic Axes that has been developed by our company for use in its vehicles. These axes, which consist of three translational and three rotational axes, represent the set of fully decoupled stiffness axes. Applying the Principal Elastic Axes to the suspension reduces the number of design parameters, which enables suspension movements to be considered totally and simply.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

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.

This paper describes the development and achievement of a target engine sound for a V6 SUV in consideration of the sound quality preferences of customers in the U.S. First, a simple definition for engine sound under acceleration was found using order arrangement, frequency balance, and linearity. These elements are the product of commonly used characteristics in conventional development and can be applied simply when setting component targets. The development focused on order arrangement as the most important of these elements, and sounds with and without integer orders were selected as target candidates. Next, subjective auditory evaluations were performed in the U.S. using digitally processed sounds and an evaluation panel comprising roughly 40 subjects. The target sound was determined after classifying the results of this evaluation using cluster analysis.

This paper describes the design, development and validation of a muffler for reducing exhaust noise from a commercial tele-handler. It also describes the procedure for modeling and optimizing the exhaust muffler along with experimental measurement for correlating the sound transmission loss (STL). The design and tuning of the tele-handler muffler was based on several factors including overall performance, cost, weight, available space, and ease of manufacturing. The analysis for predicting the STL was conducted using the commercial software LMS Virtual Lab (LMS-VL), while the experimental validation was carried out in the laboratory using the two load setup. First, in order to gain confidence in the applicability of LMS-VL, the STL of some simple expansion mufflers with and without extended inlet/outlet and perforations was considered. The STL of these mufflers were predicted using the traditional plane wave transfer matrix approach.

We developed a progressive system, “virtual and real simulator (V&R-S)” for engine. To innovate the process of engine development, the test system creates dynamic load of drivetrain, wheel, body and road with the virtual vehicle model. We set the phenomena such as drivetrain vibration for reproducing object of this system. The load is transmitted to the engine crankshaft end as torque with the connecting shaft made of fiberglass. The mainly developed technologies are the dynamometer with rotational inertia as low as engine, correction method of transmitted torque error of connecting shaft by H-infinity control. Thanks to these, we achieved the capability of optimization for most of dynamic characteristics (emission, fuel consumption, drivability) on engine test bench. And we now be able to limit real vehicle test to the final tuning. As a result, we have realized new engine evaluation and optimization process.

In FOA (First Order Analysis) any vehicle body structure might be interpreted as a collective simple structure that can be decomposed into 3 fundamental structure types. The first structure is the “BEAM”, whose cross sectional properties as well as its material dominates the mechanical behavior, the second is the “PANEL (shear panel, plate, and shell)”, whose mechanical behavior can be varied by changing its geometrical properties in the thickness direction, i.e. adding beads or flanges. The third structure is the “JOINT”, which connects the proceeding structures, and transfer complex three-dimensional loads with three-dimensional deformation. In the present work, we shall propose a methodology to identify a portion of an arbitrary FE model of an automotive body structure, with a “BEAM” structure in the FOA approach. In the latter chapter of this paper, cross section loads will be related with cross sectional properties in the aspect of the element strain energy concept.

The basic concept of the Toyota mild hybrid system is to provide a smooth and reliable engine restarting method from an idling stop, while at the same time being able to drive all of the accessories during the idling stop. This concept has been realized and marketed for the first time in the world, by utilizing a newly developed simulation of belt behavior to optimize the specification of the belt and its peripheral parts.