Multiobjective Gear Shifting Optimization Considering A Known Driving Cycle [otimização Multiobjetivo Da Troca De Marchas Em Um Ciclo De Condução Previamente Conhecido]

The reduction of the fuel consumption of the vehicles driven by combustion engines is a target of the automakers, governments and drivers. The literature asserts that the adjustment of the driver behavior results in a substantial fuel economy. Specifically, the gear shifting is one aspect of the driver behavior that can be changed by the use of support systems installed in the vehicle that indicate the right moment that the gear must be shifted. The interested community is focused on the development of the algorithms that are implemented in these support systems. These algorithms must be able to arbitrate between two antagonistic objective functions simultaneously: the maximization of the performance and the fuel economy. Thus, this paper demonstrates that it is possible to calculate the trade-off threshold between performance and fuel economy of a vehicle by means of the multiobjective optimization of the gear shifting considering a known driving cycle. To reach this objective, it is created a dynamic model of an automobile base on the literature data; the optimization algorithm implemented is Non-dominated Sorting Genetic Algorithm - II and the driving cycle used is described by the standards ABNT NBR6601:2012 and FTP-72. © 2015, Eduem - Editora da Universidade Estadual de Maringa. All rights reserved.373361369Ala-Lawi, B.M., Bradley, T.H., Analysis of corporate average fuel economy regulation compliance scenarios inclusive of plug in hybrid vehicles (2014) Applied Energy, 113, pp. 1323-1337Alam, M.S., McNabola, A., A critical review and assessment of Eco-Driving policy & technology: Benefits & limitations (2014) Transport Policy, 35, pp. 42-49Bahn, O., Marcy, M., Vaillancourt, K., Waaub, J.P., Electrification of the Canadian road transportation sector: A 2050 outlook with TIMESCanada (2013) Energy Policy, 62, pp. 593-606Banos, R., Manza-Noagugliaro, F., Montoya, F.G., Gil, C., Alcayde, A., Gómez, J., Optimization methods applied to renewable and sustainable energy: A review (2011) Renewable and Sustainable Energy Reviews, 15 (4), pp. 1753-1766Deb, K., Multi-objective optimization (2014) Search Methodologies, pp. 403-449. , BURKE, E. K.KENDALL, G. (Ed.), New York: SpringerDovgan, E., Javorski, M., Tušar, T., Gams, M., Filipič, B., Comparing a multiobjective optimization algorithm for discovering driving strategies with humans (2013) Expert Systems with Applications, 40 (7), pp. 2687-2695Dovgan, E., Tušar, T., Javorski, M., Filipic, B., Discovering Comfortable Driving Strategies Using Simulation-Based Multiobjective Optimization (2012) Informatica, 36 (3), pp. 319-326Eckert, J.J., Corrêa, F.C., Santiciolli, F.M., Costa, E.S., Dionísio, H.J., Dedini, F.G., Gear Shifting Strategies Co-simulations to Optimize Vehicle Performance and Fuel Consumption (2015) Multibody Mechatronic Systems, pp. 143-152. , CECCARELLI. M.MARTINEZ, E. E. H, Cham: Springer International PublishingGenta, G., (1997) Motor Vehicle Dynamics: Modeling and Simulation, , Singapore: World ScientificGillespie, T.D., (1992) Fundamentals of Vehicle Dynamics, , Warrendale: Society of Automotive EngineersHa, S.H., Jeon, H.T., Development of Intelligent Gear-shifting Map Based on Radial Basis Function Neural Networks (2013) International Journal of Fuzzy Logic and Intelligent Systems, 13 (2), pp. 116-123Ho, S.H., Wong, Y.D., Chang, V., Developing Singapore Driving Cycle for passenger cars to estimate fuel consumption and vehicular emissions (2014) Atmospheric Environment, 97, pp. 353-362Jasion, G., Shrimpton, J., Danby, M., Takeda, K., Performance of numerical integrators on tangential motion of DEM within implicit flow solvers (2011) Computers and Chemical Engineering, 35 (11), pp. 2218-2226Ntziachristos, L., Mellios, G., Tsokolis, D., Keller, M., Hausberger, S., Ligterink, N.E., Dilara, P., In-use vs. Type-approval fuel consumption of current passenger cars in Europe (2014) Energy Policy, 67, pp. 403-411Thiel, C., Schmidt, J., Van Zyl, A., Schmid, E., Cost and well-to-wheel implications of the vehicle fleet CO2 emission regulation in the European Union (2014) Transportation Research Part A: Policy and Practice, 63, pp. 25-42Thijssen, R., Hofman, T., Ham, J., Ecodriving acceptance: An experimental study on anticipation behavior of truck drivers (2014) Transportation Research Part F: Traffic Psychology and Behaviour, 22, pp. 249-260Vagg, C., Brace, C.J., Hari, D., Akehurst, S., Poxon, J., Ash, L., Development and field trial of a driver assistance system to encourage eco-driving in light commercial vehicle fleets. Intelligent Transportation Systems (2013) IEEE Transactions On, 14 (2), pp. 796-80