Artigo Completo - Open Access.

Idioma principal


Eckert, Jony Javorski ; Santiciolli, Fabio Mazzariol ; Costa, Eduardo dos Santos ; Corrêa, Fernanda Cristina ; Dionísio, Heron José ; Dedini, Franco Giuseppe ;

Artigo Completo:

The vehicle longitudinal dynamics is responsible for calculating the vehicle power consumption undergone a specific route, by means of the estimation of the forces acting on the system such as aerodynamic drag, rolling resistance, climbing resistance and the driver behavior. The gear shifting tactics influences the vehicle performance and fuel consumption because it changes the powertrain inertia and the engine speed. The literature presents gear-shifting strategies based on the engine power and torque as well as the fuel economy. The last tactics are difficult to determinate, because they depend on a large number of factors like vehicle speed, available transition ratios, engine efficiency, required acceleration, tire-ground traction limit and engine decoupling during the gear shifting process. This paper shows a study based on the Brazilian standard urban driving cycle NBR6601. As there are many factors involved in the vehicle behavior and also in the vehicle dynamics, it was developed an algorithm to optimize the gear shifting process: it makes a choice of the most adequate tactic for each cycle stretch. The analysis were performed by co-simulation between the multibody dynamics software AdamsTM and Matlab/SimulinkTM, in which is defined the vehicle power demand.

Artigo Completo:

Palavras-chave: ,

Palavras-chave: ,

DOI: 10.5151/engpro-simea2014-81

Referências bibliográficas
  • [1] INOVAR-AUTO. Programa de Incentivo à Inovação Tecnológica e Adensamento da Cadeia Produtiva de Veículos Automotores. 2012. Disponível em: < >. Acesso em: 10/05.
  • [2] MASHADI, B. et al. Simulation of automobile fuel consumption and emissions for various driver’s manual shifting habits. Journal of Central South University, v. 21, n. 3, p. 1058- 1066, 2014. ISSN 2095-2899.
  • [3] EHSANI, M.; GAO, Y.; EMADI, A. Modern electric, hybrid electric, and fuel cell vehicles: fundamentals, theory, and design. CRC press, 2009. ISBN 1420054007.
  • [4] KAHLBAU, S.; BESTLE, D. Optimal Shift Control for Automatic Transmission#. Mechanics Based Design of Structures and Machines, v. 41, n. 3, p. 259-273, 2013. ISSN 1539-773
  • [5] SANTICIOLLI, F. M. et al. Gear shifting optimization strategy for Brazilian vehicles and traffic. Proceedings of the 22th International Congress of Mechanical Engineering, 2013.
  • [6] VAGG, C. et al. Development of a new method to assess fuel saving using gear shift indicators. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, v. 226, n. 12, p. 1630-1639, 2012. ISSN 0954-4070.
  • [7] GUAN, T.; FREY, C. W. Fuel efficiency driver assistance system for manufacturer independent solutions. Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on: IEEE, 2012. 212-217 p.
  • [8] ORFILA, O.; SAINT PIERRE, G.; ANDRIEU, C. Gear Shifting Behavior Model for Ecodriving Simulations Based on Experimental Data. Procedia-Social and Behavioral Sciences, v. 54, p. 341-348, 2012. ISSN 1877-042
  • [9] GAO, B. et al. Observer-based clutch disengagement control during gear shift process of automated manual transmission. Vehicle System Dynamics, v. 49, n. 5, p. 685-701, 2011. ISSN 0042-3114.
  • [10] REGHUNATH, S. K.; SHARMA, D.; ATHREYA, A. S. Optimal Gearshift Strategy using Predictive Algorithm for Fuel Economy Improvement. SAE Technical Paper. 2014
  • [11] ABNT, N. Light road motor vehicles - Determination of hydrocarbons, carbon monoxide, nitrogen oxides, carbon dioxides and particulate matter in the exhaust gas. October. 28 2005.
  • [12] GILLESPIE, T. D. Fundamentals of Vehicle Dynamics. 1st. Warrendale, Pa., USA: 1992. 495
  • [13] MILLIKEN, W. F.; MILLIKEN, D. L. Race car vehicle dynamics. Society of Automotive Engineers Warrendale, 1995.
  • [14] KULKARNI, M.; SHIM, T.; ZHANG, Y. Shift dynamics and control of dual-clutch transmissions. Mechanism and Machine Theory, v. 42, n. 2, p. 168-182, 2007. ISSN 0094- 114X.
  • [15] CORRÊA, F. C.; SILVA, L.; DEDINI, F. G. Fuzzy control for hybrid vehicle. 21st Brazilian Congress of Mechanical Engineering, 2011. 9 p.
  • [16] SERRAO, L. et al. An aging model of Ni-MH batteries for hybrid electric vehicles. Vehicle Power and Propulsion, 2005 IEEE Conference: IEEE, 2005. 8 pp. p.
  • [17] LOPES, M. et al. Emissions characterization from EURO 5 diesel/biodiesel passenger car operating under the new European driving cycle. Atmospheric Environment, v. 84, p. 339- 348, 2014. ISSN 1352-2310.
  • [18] CORRÊA, F. C. et al. Implementation of heuristic control techniques in power management in hybrid vehicle parallel configuration. 2013.
  • [19] SOUZA, R. B. D. Uma visão sobre o balanço de energia e desempenho em veículos híbridos. 2010.
  • [20] ECKERT, J. J. Análise comparativa entre os métodos de cálculo da dinâmica longitudinal em veículos. 2013.
  • [21] PELLEGRINO, M. A. P. Engine Partial Loads Map for Fuel Economy Analysis Based On 15 Measured Points.
  • [22] GONZÁLEZ, F. et al. On the effect of multirate co-simulation techniques in the efficiency and accuracy of multibody system dynamics. Multibody System Dynamics, v. 25, n. 4, p. 461- 483, 2011. ISSN 1384-5640.
  • [23] SWEAFFORD, T. et al. Co-Simulation of Multiple Software Packages for Model Based Control Development and Full Vehicle System Evaluation. SAE International Journal of Passenger Cars-Mechanical Systems, v. 5, n. 1, p. 702-714, 2012. ISSN 1946-3995.
  • [24] BREZINA, T.; HADAS, Z.; VETISKA, J. Using of Co-simulation ADAMS-SIMULINK for development of mechatronic systems. MECHATRONIKA, 2011 14th International Symposium: IEEE, 2011. 59-64 p.
  • [25] AL-HAMMOURI, A. et al. A co-simulation platform for actuator networks. Proceedings of the 5th international conference on embedded networked sensor systems: ACM, 2007. 383-384 p.
  • [26] HINES, K.; BORRIELLO, G. Dynamic communication models in embedded system co-simulation. Proceedings of the 34th annual Design Automation Conference: ACM, 1997. 395-400 p.
  • [27] YIN, X.; XUE, D.; CAI, Y. Application of time-optimal strategy and fuzzy logic to the engine speed control during the gear-shifting process of AMT. Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on: IEEE, 2007. 468-472 p.
  • [28] CASAVOLA, A.; PRODI, G.; ROCCA, G. Efficient gear shifting strategies for green driving policies. American Control Conference (ACC), 2010: IEEE, 2010. 4331-4336 p.
  • [29] XI, L.; XIANGYANG, X.; YANFANG, L. Simulation of Gear-shift Algorithm for Automatic Transmission Based on MATLAB. Software Engineering, 2009. WCSE'09. WRIWorld Congress on: IEEE, 2009. 476-480 p.
  • [30] GM. Owner Manual Chevrolet Celta 2013: General Motors Brazil Ltda 2013.
Como citar:

Eckert, Jony Javorski; Santiciolli, Fabio Mazzariol; Costa, Eduardo dos Santos; Corrêa, Fernanda Cristina; Dionísio, Heron José; Dedini, Franco Giuseppe; "VEHICLE GEAR SHIFTING CO-SIMULATION TO OPTIMIZE PERFORMANCE AND FUEL CONSUMPTION IN THE BRAZILIAN STANDARD URBAN DRIVING CYCLE", p. 615-631 . In: In Anais do XXII Simpósio Internacional de Engenharia Automotica - SIMEA 2014 [=Blucher Engineering Proceedings]. São Paulo: Blucher, 2014.
ISSN 2357-7592, DOI 10.5151/engpro-simea2014-81

últimos 30 dias | último ano | desde a publicação