CLC number: TP13
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-11-15
Cited: 0
Clicked: 7294
Citations: Bibtex RefMan EndNote GB/T7714
Ming-xin Kang, Jin-wu Gao. Design of an eco-gearshift control strategy under a logic system framework[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(2): 340-350.
@article{title="Design of an eco-gearshift control strategy under a logic system framework",
author="Ming-xin Kang, Jin-wu Gao",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="2",
pages="340-350",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1900459"
}
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%A Ming-xin Kang
%A Jin-wu Gao
%J Frontiers of Information Technology & Electronic Engineering
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%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1900459
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T1 - Design of an eco-gearshift control strategy under a logic system framework
A1 - Ming-xin Kang
A1 - Jin-wu Gao
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
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%@ 2095-9184
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1900459
Abstract: Good access to traffic information provides enormous potential for automotive powertrain control. We propose a logical control approach for the gearshift strategy, aimed at improving the fuel efficiency of vehicles. The driver power demand in a specific position usually exhibits stochastic features and can be statistically analyzed in accordance with historical driving data and instant traffic conditions; therefore, it offers opportunities for the design of a gearshift control scheme. Due to the discrete characteristics of a gearshift, the control design of the gearshift strategy can be formulated under a logic system framework. To this end, vehicle dynamics are discretized with several logic states, and then modeled as a logic system with the Markov process model. The fuel optimization problem is constructed as a receding-horizon optimal control problem under the logic system framework,and a dynamic programming algorithm with algebraic operations is applied to determine the optimal strategy online. Simulation results demonstrate that the proposed control design has better potential for fuel efficiency improvement than the conventional method.
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