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Optimization of Matching Between Mechanics and Thermodynamics – Approach for Engine Efficiency Improvement

American Bureau of Shipping (ABS)-Changhua He
Heihe Technology Inc-Yuanping Zhao
  • Technical Paper
  • 2020-01-0799
To be published on 2020-04-14 by SAE International in United States
The relationship between engine mechanics and thermodynamics is investigated in this paper. By means of numerical simulation, the inherent mismatching between the mechanics behaviors and the thermodynamic process in internal combustion engines is revealed, which is believed to be the main limiting factor of energy efficiency for the engines available in the current market. A design concept is proposed for engine efficiency improvement - Optimization of matching between engine mechanics and thermal dynamics. A parameter of Matching Gain is defined for quantifying engine efficiency improvement by comparing with a baseline engine. Several case studies have been conducted toward the actual designs in the history of engine development. The reasons for positive gains achieved as well as for negative results obtained are interpreted with the matching concept. Based on the results unveiled by this approach, it is reasonable to predict that an ideal engine with Optimal Matching Between Mechanics and Thermodynamics exists. The matching concept could be used as a guideline for engine efficiency improvement. A concept engine design with the matching approach is under development.
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Development of New Hybrid Transaxle for Mid-Size Sports Utility Vehicles

Toyota Motor Corporation-Seitaro Nobuyasu, Shigetsugu Iwata, Masabumi Nishigaya, Yoshiteru Hagino, Masatoshi Ito, Hiroshi Aihara
  • Technical Paper
  • 2020-01-0850
To be published on 2020-04-14 by SAE International in United States
Recently, automotive industries are active to develop electric in response to the energy conservation and environment problems. We developed the new hybrid transaxle for Mid-Size SUV to improve fuel efficiency and power performance. The transaxle was developed based on the new development strategy TNGA (Toyota New Global Architecture). By adopting technologies for transaxle overall length shortening, installation in same width of Mid-Size sedan engine compartment have been realized while improving the motor output. This paper will explain technologies about new motor structure and new mount structure for overall length shortening, and furthermore, noise reduction toward the mount structure.
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Evaluating the Performance of a Conventional and Hybrid Bus operating on Diesel and B20 Fuel for Emissions and Fuel Economy

U.S. Environmental Protection Agency-Scott Ludlam
US Environmental Protection Agency-Matthew Brusstar
  • Technical Paper
  • 2020-01-1351
To be published on 2020-04-14 by SAE International in United States
With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric buses are considered as a potential solution as they are perceived to be less polluting and more fuel-efficient than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL), the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 80,000 lbs) may be evaluated under controlled conditions in the heavy-duty chassis dynamometer test. The present study evaluated the performance of a conventional bus and hybrid bus for emissions and fuel economy under representative test cycles (including cold start and hot start conditions) with Diesel (#2) and Biodiesel (B20) fuel. The conventional bus was equipped with a Cummins ISL 8.3L engine and a Diesel Particulate Filter (DPF) and Diesel Oxidation Catalyst…
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Energy Efficient Maneuvering of Connected and Automated Vehicles

Southwest Research Insitute-Michael Gross
Southwest Research Institute-Sankar Rengarajan, Scott Hotz, Jayant Sarlashkar, Stanislav Gankov, Piyush Bhagdikar, Charles Hirsch
  • Technical Paper
  • 2020-01-0583
To be published on 2020-04-14 by SAE International in United States
Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies will allow a vehicle to "know" its future operating conditions with some degree of certainty, greatly narrowing prior information gaps. The increased development of such Connected and Automated Vehicle (CAV) systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles. The NEXTCAR program is one such initiative by the Advanced Research Projects Agency – Energy (ARPA-E) to developed advanced vehicle dynamics and powertrain control technologies that leverage such connected information streams. Southwest Research Institute (SwRI) in collaboration with Toyota and University of Michigan is currently working on improving energy consumption of a Toyota Prius Prime 2017 by 20%. This paper provides an overview of the various algorithms that have been developed to achieve the energy consumption target. A breakdown of how individual algorithms contribute to the overall target is presented. The team built a specialized test-bed called CAV dynamometer that integrates a traffic simulator and a hub dynamometer for testing the…
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Vehicle Velocity Prediction Using Artificial Neural Network and Effect of Real World Signals on Prediction Window.

CEAS Western Michigan University-Alvis Fong
Colorado State Univ-Thomas Bradley, Lowell Hanson
  • Technical Paper
  • 2020-01-0729
To be published on 2020-04-14 by SAE International in United States
Prediction of vehicle velocity is important since it can realize improvements in the fuel economy/energy efficiency, drivability and safety. Velocity prediction has been addressed in many publications. Several references considered deterministic and stochastic approaches such as Markov chain, autoregressive models, and artificial neural networks. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain inclusive datasets. Using these inclusive datasets of sensors in deep neural networks, high accuracy velocity predictions can be achieved. This research builds upon previous findings that Long Short-Term Memory (LSTM) deep neural networks provide the highest velocity prediction fidelity. We developed LSTM deep neural network which uses different groups of datasets collected in Fort Collins. Synchronous data was gathered using a test vehicle equipped with sensors to measure ego vehicle position and velocity, ADAS-derived near-neighbor relative position and velocity, and infrastructure-level transit time and signal phase and timing. Effect of different group of datasets on forward velocity prediction window of 10, 15, 20 and 30 seconds is studied. Developed algorithm is tested…
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Leveraging real-world driving data sets for design and impact evaluation of energy efficient control strategies.

General Motors-Bharatkumar Hegde, Steven E. Muldoon
National Renewable Energy Laboratory-Michael O'Keefe, Jeff Gonder
  • Technical Paper
  • 2020-01-0585
To be published on 2020-04-14 by SAE International in United States
Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are non-causal and are typically intended for evaluating emission and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies. In this study, we present two methods of leveraging real-world data in both design optimization of energy efficient control strategies and in evaluating the real-world impact of those control strategies upon large-scale deployment. Through these methodologies, strategies with highest impact on energy savings were selected…
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Data-driven framework for fuel efficiency improvement in extended range electric vehicle used in package delivery applications

Univ of Minnesota-Twin Cities-Pengyue Wang, William Northrop
  • Technical Paper
  • 2020-01-0589
To be published on 2020-04-14 by SAE International in United States
Extended-range electric vehicles (EREVs) are a potential solution for fossil fuel usage mitigation and on-road emissions reduction. EREVs can be shown to yield significant fuel economy improvements when the proper energy management strategies (EMSs) are employed. However, many in-use EREVs achieve only moderate fuel reduction compared to conventional vehicles due to the fact that their EMS is far from optimal. This paper focuses on rule-based optimization methods to improve the fuel efficiency of EREV last-mile delivery vehicles equipped with two-way Vehicle-to-Could (V2C) connectivity. The method uses previous vehicle data collected on actual delivery routes and a machine learning method to improve the fuel economy of future routes. The paper first introduces the main challenges of the project such as inherent uncertainty in human driver behavior and in the roadway environment. Then, the framework of our practical physics-model guided data-driven approach is introduced. For vehicles with small amounts of previous data, a Bayesian method is used to adjust a control parameter in the EMS offline for each vehicle with introduced prior information derived from large numbers…
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Impact of different types of glazing on Air- Conditioning system performance of vehicle

Maruti Suzuki India, Ltd.-Akshay Bhateja
  • Technical Paper
  • 2020-01-1249
To be published on 2020-04-14 by SAE International in United States
Due to intense peak summer temperatures and sunny summers in tropical countries like India, achieving the required cabin temperature in vehicle without compromising on fuel efficiency is becoming increasingly challenging. The major source of heat load on vehicle is solar load. Therefore, a study has been conducted to evaluate the heat load on vehicle cabin due to solar radiations and its impact on vehicle Air-Conditioning system performance with various combinations of door glasses and windscreen. The glasses used for this study are classified as Green, Dark Green, Dark Gray, Standard PVB (Polyvinyl Butyral) Windscreen and PVB Windscreen having Infrared Cut particles. For each glass, part level evaluation was done to find out the percentage transmittance of light of different wavelengths and percentage transmittance of heat flux through each glass. To verify the effectiveness of each glass, vehicle level Air-Conditioning system performance test was done in All Weather Chassis Dyno Facility for each retrofitted vehicle. Retrofitted vehicle configurations were decided as per regional visible light transmittance regulations. To eliminate the effect of manufacturing variance while evaluating…
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Material development for low viscosity oil

NOK Corporation-Keita Otani, Kenichi Kunieda, Yuki Sato
  • Technical Paper
  • 2020-01-0232
To be published on 2020-04-14 by SAE International in United States
In recent years, it is a big trend to decrease oil viscosity as regards in the drive-train system in order to progress the fuel efficiency by reducing frictional loss of each mechanical unit. However, we found that the oil-seal performance get worse in cold environment with applying the low viscosity oil, and it leads to oil leakage. The presumed mechanism is that the rubber material used in the oil-seal loses its flexibility at a low temperature to deteriorate the shaft runout followability, while the low viscosity oil can flow even such environment. Concerning rubber material, acrylic rubber (ACM) is widely used as a seal component for automobiles including drive-train system because it has a good balance of heat resistance, cold resistance, and oil resistance. As results of investigation low viscosity oil under development using our lineup ACM which has excellent low temperature property (TR-10:-37℃), we confirmed that the shaft runout limit deteriorates with decrease oil viscosity, and this result shows the need of further enhanced rubber material. In this study, we describe the improvement in…
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Estimation of Fuel Economy on Real-Word Routes for Next-Generation Connected and Automated Hybrid Powertrains

Delphi Technologies-John Kirwan, Pete Olin
Delphi Technologies Inc-Karim Aggoune
  • Technical Paper
  • 2020-01-0593
To be published on 2020-04-14 by SAE International in United States
The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although, the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods. This paper describes a methodology to properly benchmark the fuel consumption reduction potential of advanced cylinder deactivation and 48V mild hybridization in the presence of Level 1 connectivity and automation, and including accounting for the…