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The development of JASO GLV-1 -Next Generation Low Viscosity automotive Gasoline Engine Oils Specification

Toyota Motor Corp.-Kazuo Yamamori, Satoshi Hirano
Infineum Japan, Ltd.-Taisuke Miyoshi
  • Technical Paper
  • 2020-01-1426
To be published on 2020-04-14 by SAE International in United States
It is a common understanding that reducing engine oil viscosity has a great effect on improving fuel economy. However, it has been impossible to evaluate ultra low viscosity engine oil below SAE 0W-12 utilizing the existing fuel economy test method and there is no specification for ultra low viscosity gasoline engine oil. Therefore, we developed firing and motored fuel economy test methods using Japanese automobile manufactures’ engines for ultra low viscosity oil at the Task Force (hereafter called TF) mainly consist of Japanese automobile and petroleum industry. Furthermore, the TF developed JASO GLV-1 specification including these fuel economy tests for next generation ultra low viscosity automotive gasoline engine oils such as SAE 0W-8 and 0W-12. In development of JASO GLV-1 specification, Japanese fuel economy tests and ILSAC engine tests for engine robustness evaluation were used. The fuel economy and engine robustness tests of four reference oils (two of them were SAE 0W-8 and others were SAE 0W-16) and three demonstration oils (SAE 0W-8) were evaluated to examine whether it was possible to evaluate SAE 0W-8…
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Model Based Control for Premixed Charge Compression Ignition Diesel Engine

Toyota Motor Corp.-Kentaro Nishida, Hajime Shimizu
  • Technical Paper
  • 2020-01-1150
To be published on 2020-04-14 by SAE International in United States
Premixed charge compression ignition (PCCI) combustion is effective to reduce diesel engine harmful exhaust gas and improve fuel consumption. However, PCCI combustion has a problem of low combustion stability compared to diesel diffusive combustion, and there are few examples of application to mass production engines. In addition to engine speed and load, it needs complicated injection control according to environmental conditions such as outside air temperature, pressure, and engine water temperature, and transient changes such as supercharging delay, EGR delay, and intake air temperature delay. Although there is example where the control maps are switched according to the intake condition, it needs huge maps considering all the parameters mentioned above. Thus it requires a significant calibration man-hour. And this may lead to deterioration of reliability such as combustion noise and torque fluctuation. In this study, the physical model is applied to calculate the ignitability in the cylinder cycle by cycle, and the ignition delay is controlled according to the ignitability changing injection pattern, thereby eliminating a huge control maps. And this can improve the calibration…
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Study of simple detection of gasoline fuel contaminants contributing to increase Particulate Matter Emissions

Toyota Motor Corp.-Yutaka Iida, Takashi Nomura
IFP Energies Nouvelles-Arij Ben Amara, Marion Lacoue-Negre, David Goncalves, Melinda Tebib, Isabelle Leveque, Vincent Souchon, Mickael Matrat, Laurie Starck
  • Technical Paper
  • 2020-01-0384
To be published on 2020-04-14 by SAE International in United States
The reduction of particulate emissions is one of the most important challenges facing the development of future gasoline engines. Several studies have demonstrated the impact of fuel chemical composition on the emissions of particulate matter, more particularly, the detrimental effect of high boiling point components such as heavy aromatics. Fuel contamination is likely to become a critical issue as new, more stringent regulations such as Real Driving Emissions RDE with market fuel. The objective of this study is to investigate several experimental approaches to detect the presence of Diesel fuel in Gasoline which is likely to alter pollutant emissions. To achieve this, a fuel matrix composed of 14 fuels was built presenting diesel fuel in varying concentrations from 0.1 to 2% v/v. The fuel matrix was characterized using several original techniques developed in this study. These are Near Infrared spectroscopy (NIR) associated to Principal Component Analysis (PCA) and Partial Least Square (PLS) modelling, micro-filtration. Their capacity to identify diesel fuel was compared to standard methods, such as, distillation, washed and unwashed gums, high boiling components…
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Development of an Analytical Method for Rear Differential Gear Whine Noise Utilizing Principal Component Contribution by OTPA and CAE

Toyota Motor Corp.-Miho Nakatsuka, Tetsuya Miwa
Osaka Institute of Technology-Junji Yoshida
Published 2019-06-05 by SAE International in United States
The progress of vehicle electrification has reduced engine noise and the improvement of rear differential gear whine noise has become more important for customer satisfaction. Rear differential gear whine noise is a result of the vibration generated by the transmission error of the gears transmitted to the cabin from various paths. As several components have a contribution, identifying key paths to develop an effective countermeasure becomes time consuming.Operational transfer path analysis (OTPA) is one of the TPA methods to determine the main path and contributing part using only the operational data. However, in cases where many reference points are set on the same frame or body, the contribution becomes similar because of high correlation between the reference data set. As a result, finding the main transfer path becomes difficult. To overcome this issue, the principal component (PC) contribution obtained from the correlated reference signals was established by modifying the OTPA process. Through this process, important vibration behavior of the target structure can be obtained as the high contributing PC mode. In this paper, this approach…
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Effects of the Feature Extraction from Road Surface Image for Road Induced Noise Prediction Using Artificial Intelligence

Toyota Motor Corp.-Shunsuke Nakamura, Masashi Komada, Keisuke Ishizaki
Gifu University-Yuichi Matsumura, Kojiro Matsushita
Published 2019-06-05 by SAE International in United States
Next generation vehicles driven by motor such as electric vehicles and fuel cell vehicles have no engine noise. Therefore the balance of interior noise is different from the vehicles driven by conventional combustion engine. In particular, road induced noise tends to be conspicuous in the low to middle vehicle speed range, therefore, technological development to reduce it is important task. The purpose of this research is to predict the road induced noise from the signals of sensors adopted for automatic driving for utilizing the prediction result as a reference signal to reduce road induced noise by active noise control (ANC). Using the monocular camera which is one of the simplest image sensors, the road induced noise is predicted from the road surface image ahead of the vehicle by machine learning. The effects to extract features (Histograms of Oriented Gradients (HOG) feature, autoencoder feature, Convolutional Neural Network (CNN) feature) from road surface images are evaluated by visualization result of t-SNE. From the features acquired by the above method, the frequency characteristics of the road induced noise…
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Machine Learning Based Technology for Reducing Engine Starting Vibration of Hybrid Vehicles

Toyota Motor Corp.-Kento Shimode, Keisuke Ishizaki, Masashi Komada
Published 2019-06-05 by SAE International in United States
Engine starting vibration of hybrid vehicle with Toyota hybrid system has variations even in the same vehicle, and a large vibration that occurs rarely may cause stress to the passengers. The contribution analysis based on the vibration theory and statistical analysis has been done, but the primary factor of the rare large vibration has not been clarified because the number of factors is enormous. From this background, we apply machine learning that can reproduce multivariate and complicated relationships to analysis of variation factors of engine starting vibration. Variations in magnitude of the exciting force such as motor torque for starting the engine and in-cylinder pressure of the engine and timing of these forces are considered as factors of the variations. In addition, there are also nonlinear factors such as backlash of gears as a factor of variations. For the variation factor analysis, it is difficult to measure the physical quantities mentioned above from experiments, because of the high time load of installing measuring sensors and lack of measurement technology for some factors. On the other…
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Determine 24 GHz and 77 GHz Radar Characteristics of Surrogate Grass

Toyota Motor Corp.-Rini Sherony
Indiana University; Purdue University-Jun Lin, Stanley Chien, Qiang Yi, Yaobin Chen
Published 2019-04-02 by SAE International in United States
Road Departure Mitigation System (RDMS) is a new feature in vehicle active safety systems. It may not rely only on the lane marking for road edge detection, but other roadside objects This paper discusses the radar aspect of the RDMS testing on roads with grass road edges. Since the grass color may be different at different test sites and in different seasons, testing of RDMS with real grass road edge has the repeatability issue over time and locations. A solution is to develop surrogate grass that has the same characteristics of the representative real grass. Radar can be used in RDMS to identify road edges. The surrogate grass should be similar to representative real grass in color, LIDAR characteristics, and Radar characteristics. This paper provides the 24 GHz and 77 GHz radar characteristic specifications of surrogate grass.
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Application of Dynamic Mode Decomposition to Influence the Driving Stability of Road Vehicles

Toyota Motor Corp.-Yusuke Nakae, Hiroshi Tanaka
Altair Engineering-Daiki Matsumoto, Christoph Niedermeier
Published 2019-04-02 by SAE International in United States
The recent growth of available computational resources has enabled the automotive industry to utilize unsteady Computational Fluid Dynamics (CFD) for their product development on a regular basis. Over the past years, it has been confirmed that unsteady CFD can accurately simulate the transient flow field around complex geometries. Concerning the aerodynamic properties of road vehicles, the detailed analysis of the transient flow field can help to improve the driving stability. Until now, however, there haven’t been many investigations that successfully identified a specific transient phenomenon from a simulated flow field corresponding to driving stability. This is because the unsteady flow field around a vehicle consists of various time and length scales and is therefore too complex to be analyzed with the same strategies as for steady state results. Dynamic Mode Decomposition (DMD) extracts the coherent structures from complex, transient flow fields, which can help to identify certain target phenomena. However, one issue in the practical application of DMD is the difficulty to find a connection between a computed mode and an actual aerodynamic effect on…
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Effect of High RON Fuels on Engine Thermal Efficiency and Greenhouse Gas Emissions

Toyota Motor Corp.-Nozomi Yokoo, Koichi Nakata
ExxonMobil Fuels and Lubricants Co.-Abdelhadi Sahnoune
Published 2019-04-02 by SAE International in United States
Historically, greenhouse gas (GHG) emissions standards for vehicles have focused on tailpipe emissions. However, sound environmental policy requires a more holistic well-to-wheels (WTW) assessment that includes both production of the fuel and its use in the vehicle. The present research explores the net change in WTW GHG emissions associated with moving from regular octane (RO) to high octane (HO) gasoline. It considers both potential increases in refinery emissions from producing HO fuel and potential reductions in vehicle emissions through the use of fuel-efficient engines optimized for such fuel. Three refinery configurations of varying complexity and reforming capacity were studied. A set of simulations covering different levels of HO gasoline production were run for each refinery configuration. Two engine designs were considered: one which could take little advantage of higher octane fuel to increase efficiency, and one which could be adjusted further to take advantage of the higher octane. WTW GHG emissions were analyzed within a life cycle analysis framework, where the upstream emissions of raw material and utility inputs to the refinery were added to…
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Has Electronic Stability Control Reduced Rollover Crashes?

Toyota Motor Corp.-Rini Sherony
Virginia Tech-Luke Riexinger, Hampton Gabler
Published 2019-04-02 by SAE International in United States
Vehicle rollovers are one of the more severe crash modes in the US - accounting for 32% of all passenger vehicle occupant fatalities annually. One design enhancement to help prevent rollovers is Electronic Stability Control (ESC) which can reduce loss of control and thus has great promise to enhance vehicle safety. The objectives of this research were (1) to estimate the effectiveness of ESC in reducing the number of rollover crashes and (2) to identify cases in which ESC did not prevent the rollover to potentially advance additional ESC development.All passenger vehicles and light trucks and vans that experienced a rollover from 2006 to 2015 in the National Automotive Sampling System Crashworthiness Database System (NASS/CDS) were analyzed. Each rollover was assigned a crash scenario based on the crash type, pre-crash maneuver, and pre-crash events. The Insurance Institute for Highway Safety ESC availability database was matched to each NASS/CDS case vehicle by the vehicle make, model, and model year. ESC effectiveness was computed using the quasi-induced exposure method.From 2006-2015, control loss was a factor in 29.7%…
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