Optimization of fuel consumption and NOx emission for mild HEV via hierarchical model predictive control

In this paper, we consider the fuel economy optimization problem for a mild hybrid electric vehicle (HEV) using hierarchical model predictive control. In the proposed algorithm, two problems are addressed: eco-driving and torque distribution. In the eco-driving problem, vehicle speed was controlled....

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Bibliographic Details
Published in:Control theory and technology 2022, Vol.20 (2), p.221-234
Main Authors: Umezawa, Yuka, Yamauchi, Ken, Seto, Hiroki, Imamura, Toshiro, Namerikawa, Toru
Format: Article
Language:English
Subjects:
Algorithms
Complexity
Computational Intelligence
Control
Control and Systems Theory
Emissions
Engineering
Fuel consumption
Fuel economy
Hybrid electric vehicles
Mathematical models
Mechatronics
Optimization
Predictive control
Research Article
Robotics
Systems Theory
Torque
Traffic speed
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Summary:In this paper, we consider the fuel economy optimization problem for a mild hybrid electric vehicle (HEV) using hierarchical model predictive control. In the proposed algorithm, two problems are addressed: eco-driving and torque distribution. In the eco-driving problem, vehicle speed was controlled. Considering the reduction in fuel consumption and NO x emissions, the torque required to follow the target speed was calculated. Subsequently, in the torque distribution problem, the distribution between the engine and motor torques were calculated. In this phase, engine characteristics were considered. These problems differ in terms of time scales; therefore, a hierarchical model predictive control is proposed. Lastly, the numerical simulation results demonstrated the efficacy of this research.
ISSN:2095-6983
2198-0942
DOI:10.1007/s11768-022-00097-9