1、The Best of COMVEC 2016 Select Technical Papers from the SAE Commercial Vehicle Engineering CongressOther SAE books of interest: Data Acquisition from HD Vehicles Using J1939 CAN Bus Eric Walter and Richard Walter (Product Code: R-446) Advanced Hybrid Powertrains for Commercial Vehicles Haoran Hu, S
2、imon Basely, Rudolf M. Smaling (Product Code: R-396) Fleet Services Managing to Redefine Success Tim King (Product Code: R-447) Finite Element Analysis for Design Engineers, Second Edition Paul M. Kurowski (Product Code: R-449) Successful Prediction of Product Performance Lev Klyatis (Product Code:
3、R-448) Aerodynamics of Road Vehicles, Fifth Edition Thomas Chrisitian Schuetz (Product Code: R-430) Brake Technology Handbook Karlheinz Bill and Bert J. Breuer (Product Code: R-375) Onboard Diagnostics and Measurement in the Automotive Industry, Shipbuilding, and Aircraft Construction Michael Palocz
4、-Andresen (Product Code: R-410) For more information or to order a book, contact: SAE INTERNATIONAL 400 Commonwealth Drive Warrendale, PA 15096 Phone: +1.877.606.7323 (U.S. and Canada only) or +1.724.776.4970 (outside U.S. and Canada) Fax: +1.724.776.0790 Email: CustomerServicesae.org Website: books
5、.sae.orgThe Best of COMVEC 2016 Select Technical Papers from the SAE Commercial Vehicle Engineering Congress Edited by Kevin Jost, Dr. Corina Sandu, and Ryan Gehm Warrendale, Pennsylvania, USACopyright 2016 SAE International. All rights reserved. No part of this publication may be reproduced, stored
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11、stomerServicesae.org Phone: +1.877.606.7323 (inside USA and Canada) +1.724.776.4970 (outside USA) Fax: +1.724.776.0790v Table of Contents Introduction . vii Autonomous Driving in Agriculture Leading to Autonomous Worksite Solutions (2016-01-8006) 1 John Reid and Stewart Moorehead, Deere Alex Foessel
12、, John Deere Brasil SA; Julian Sanchez, John Deere CFD Comparison with Wind-Tunnel for a Class 8 Tractor-Trailer (2016-01-8140) 7 Devaraj Dasarathan, Exa Corporation; Ashraf Farag, Navistar; Matthew Ellis, Exa Corporation The Evaluation of the Impact of New Technologies for Different Powertrain Medi
13、um-Duty Trucks on Fuel Consumption (2016-01-8134) 15 Lijuan Wang, Adam Duran, Kenneth Kelly, Arnaud Koana, Michael Lammert, and Robert Prohaska, National Renewable Energy Laboratory Evaluation of System Configurations for Downsizing a Heavy-Duty Diesel Engine for Non-Road Applications (2016-01-8058)
14、 23 Mufaddel Dahodwala, Satyum Joshi, Hari Krishnamoorthy, Erik W. Koehler, and Michael Franke, FEV NA, Inc. Pneumatically Shifted Air Suspension Loading for Improved Fuel Economy Benefits (2016-01-8031) . 37 Nicholas Atanasov and Evan Chenoweth, Daimler Trucks North America LLC New MAHLE Steel Pist
15、on and Pin Coating System for Reduced TCO of CV Engines (2016-01-8066). 45 Marco Maurizi and Daniel Hrdina, Mahle GmbH Testing of a Long Haul Demonstrator Vehicle with a Waste Heat Recovery System on Public Road (2016-01-8057) 51 Michael Glensvig, Heimo Schreier, Mauro Tizianel, and Helmut Theissl,
16、AVL List GmbH; Peter Krhenbhl and Fabio Cococcetta, FPT Motorenforschung AG; Ivan Calaon, Iveco Fan Shroud Optimization Using Adjoint Solver (2016-01-8070) 61 Prasad Vegendla and Tanju Sofu, Argonne National Laboratory; Rohit Saha, Mahesh Madurai Kumar, and Long-Kung Hwang, Cummins Inc.; Steven Dowd
17、ing, CD-Adapcovi Towards a Cyber Assurance Testbed for Heavy Vehicle Electronic Controls (2016-01-8142) 67 Jeremy Daily, Rose Gamble, Stephen Moffitt, Connor Raines, Paul Harris, and Jannah Miran, University of Tulsa; Indrakshi Ray, Subhojeet Mukherjee, and Hossein Shirazi, Colorado State University
18、; James Johnson, Synercon Technologies Estimation of Excavator Manipulator Position Using Neural Network-Based Vision System (2016-01-8122) . 79 Jiaqi Xu and Hwan-Sik Yoon, The University of Alabama; Jae Y. Lee and Seonggon Kim, Volvo Construction Equipment About the Editors 89vii The Best of COMVEC
19、 2016 Select Technical Papers from the SAE Commercial Vehicle Engineering Congress Welcome to the first of its kind special publication highlighting some of the best technical papers from an SAE technical conference. This publication, focusing on select papers from the 2016 SAE Commercial Vehicle En
20、gineering Congress (COMVEC), was developed by the SAE Automotive and Commercial Vehicle Product Group in partnership with the SAE Journals and Media groups. Its creation would not have been possible without significant input from Dr. Corina Sandu, the Editor-in-Chief for the SAE International Journa
21、l of Commercial Vehicles, and Ryan Gehm, Editor-in-Chief of SAEs Off-Highway Engineering magazine. The purpose of this compilation of papers is to highlight the breadth of the entire COMVEC technical program from a corporate contribution perspective along with the specific focus of the 2016 events t
22、heme of connectivity. Helping to shape the events program was Dr. Wilfried Achenbach, Senior Vice President, Engineering and Technology, Daimler Trucks North America (DTNA) who is fulfilling the events Executive Leadership role this year, and other executives from DTNA. This years COMVEC adds a new
23、symposia format to the traditional technical program with technical papers and associated presentations focused on autonomous commercial vehicles and meeting the challenges of Phase 2 greenhouse gas (GHG) emissions for on-road trucks. The leadership team focused on attracting a broader mixture of pa
24、rticipants to COMVEC, emphasizing the importance of bringing together governmental agencies, academics and industry partners to discuss challenges for the future. The commercial vehicle industry has always been focused on improving efficiency to lower customers total operating costs, and government
25、regulation has only sharpened the focus on efficiency and emissions. The U.S. EPA and NHTSA recently issued the final Phase 2 GHG standards. The agencies expect the new rules to save more than one billion metric tons of Co 2emissions and two billion barrels of oil. They also estimate the new “techno
26、logy advancing” standards will save medium- and heavy-duty vehicle owners $170 billion over the life or the program, which covers model years 2021-2027. Emerging technologies not yet in widespread use are essential to satisfy Phase 2. Technology supporting autonomous driving has been and will contin
27、ue to impact the commercial vehicle industry. Industry investments in autonomous driving technology has grown rapidly, leaving a wide range of opinions on how the future of autonomous operation will look. The first paper of this publication (2016-01-8006) focuses on autonomous commercial vehicles fr
28、om the John Deere perspective. It starts with a focus on the transformation of agriculture at the beginning of this century, as automated steering of agricultural machine systems increased the productivity and convenience in crop production systems. Integrated worksite solutions through machine and
29、information management continue to transform agriculture. This precursor to fully autonomous solutions will lead to the optimization of the worksite ecosystem. Recent regulations on GHG emissions standards have prompted standardized procedures for assessing the aerodynamic performance of Class 8 tra
30、ctor-trailers. The coast-down test procedure is currently the primary reference method employed to assess vehicle drag, while other valid alternatives include constant speed testing, computational fluid dynamics (CFD) simulations, and wind-tunnel testing. Engineers at Exa Corp. and Navistar have inv
31、estigated the aerodynamics and simulation for heavy-duty, on-road applications via CFD and compared results with wind-tunnel testing of a Class 8 tractor-trailer. The main purpose of their paper, 2016-01-8140, is to compare CFD simulations with a corresponding 1/8 th -scale wind-tunnel test. Additio
32、nally, the paper highlights the impacts of wind-tunnel testing on the total drag coefficient performance as compared to full-scale open-road analysis with and without real world, upstream turbulence wind conditions. Evaluating the fuel consumption impact of new technologies over a range of medium-du
33、ty parcel delivery powertrain configurations is the focus of a U.S. National Renewable Energy Laboratory paper (2016-01-8134). Results of simulation studies are presented to evaluate potential fuel savings as a result of improvements to vehicle rolling resistance, coefficient of drag, and vehicle we
34、ightas well as hybridizationfor four powertrains. The vehicles were modeled and simulated over 1290 real-world driving trips to determine the fuel savings potential based on improvements to each technology and to identify best- use cases for each platform. Fuel consumption and emissions reduction ha
35、ve been two of the primary drivers in recent years of successful application of engine downsizing in the passenger-car and heavy-duty on-highway markets, motivated in part by CO 2emissions limits and Phase 1 GHG legislation. There has been less activity for off-highway applications, but now research
36、ers are investigating downsizing to improve fuel economy, reduce purchase price, and provide packaging and machine layout improvement opportunities in off-road machines. FEV NA engineers have evaluated system configurations for downsizing heavy-duty diesel engines for non-road applications (2016-01-
37、8058). Various technologies, such as electrically assisted turbocharger, two-stage turbocharging, asymmetric twin scroll turbine and variable valve actuation, were investigated to maintain performance requirements while reducing the number of cylinders. The fuel economy benefits of pneumatically shi
38、fted air- suspension loading are explored in a paper by engineers at Daimler Trucks North America LLC (2016-01-8031). viii Introduced on heavy-duty trucks in the 1990s, electronically controlled air-suspension systems have seen little in the way of major improvements since then, according to Daimler
39、 engineers. However, a need exists for intelligently controlled air suspension systems, specifically those that can be applied to 6x2 axle configurations in the North American market. The major novelty of the Daimler concept is that, by using specific axle configurations and tires, a shift in pressu
40、re from the driven to the non-driven axles may result in improvements in overall vehicle fuel economy. A noticeable improvement was demonstrated, lowering fuel costs for operators and reducing vehicle environmental impact. Total cost of ownership (TCO) is requiring further improvements to piston fri
41、ction reduction as well as additional gains in thermal efficiency. Mahle has developed a new steel piston and pin coating system for reduced TCO of commercial vehicle engines (2016-01-8066). A piston compression height reduction in combination with carbon-based piston pin coatings is enabling the ad
42、vancements. The company implemented an innovative metal-joining technology using laser welding to generate a cooling gallery. The MonoLite concept offers an optimum design and position of the cooling gallery as well as durability for high peak cylinder pressures that are advantageous for complex com
43、bustion-bowl geometries needed in modern diesel engines to meet fuel economy and emissions requirements. New simulation and testing techniques are enabling the next generation of commercial vehicle technology. Engineers at AVL List GmbH, FPT Motorenforschung AG, and Iveco are presenting the results
44、of a long-haul truck waste heat recovery (WHR) system from simulation, test bench, and public road testing (2016-01-8057). The WHR system uses exhaust gas recuperation and up to 110 kW of exhaust waste heat in an Organic Rankine Cycle (ORC) in a typical European driving cycle. The testing and simula
45、tion of different real-life European and U.S. cycles indicate fuel-consumption benefits of between 2.5% and 3.4%. A technology road map discusses the role of WHR in fulfilling the future California Air Resources Board Brake-Specific Fuel Consumption (CARB BSFC) target value (minimum in map) of aroun
46、d 172 g/kWh. Simulation advancements are also shown in a fan shroud optimization by researchers at Argonne National Laboratory, Cummins Inc., and CD-Adapco using software (2016-01- 8070). Fan and fan-shroud design are critical for underhood airflow management, so the work was aimed at demonstrating
47、a method to maximize cooling air-mass flow rates through the heat exchangers using CD-Adapcos Adjoint Solver in STAR-CCM+. An overall 1.4% increase in cooling air-mass flow was observed in the heat exchanger with the optimized/ morphed fan-shroud surface. Further evaluation is under way to maximize
48、the cooling air mass flow benefit. Cybersecurity assurance of heavy trucks is a major concern with new designs as well as with supporting legacy systems. To help connect security and heavy-truck researchers, a remotely accessible testbed has been prototyped for experimentation to evaluate and improv
49、e upon existing technologies as well as develop domain-specific technologies. The testbeddescribed in a paper by University of Tulsa, Colorado State University, and Synercon Technologies (2016- 01-8142)relies on embedded Linux-based node controllers that can simulate sensor inputs to various heavy-vehicle electronic control units. How the testbed can be used for security research is presented along with an example of its use in evaluating seed/key exchange strength and in intrusion detection systems. Finally, researchers at the University of Alabama and Volvo Construction
