Battery thermal management strategy for electric vehicles based on nonlinear model predictive control

Measurement ◽  
2021 ◽  
Vol 186 ◽  
pp. 110115
Author(s):  
Yan Ma ◽  
Hao Ding ◽  
Hongyuan Mou ◽  
Jinwu Gao
Author(s):  
Jorge Lopez Sanz ◽  
Carlos Ocampo-Martinez ◽  
Jesus Alvarez-Florez ◽  
Manuel Moreno Eguilaz ◽  
Rafael Ruiz-Mansilla ◽  
...  

2017 ◽  
Vol 66 (9) ◽  
pp. 7751-7760 ◽  
Author(s):  
J. Lopez-Sanz ◽  
Carlos Ocampo-Martinez ◽  
Jesus Alvarez-Florez ◽  
Manuel Moreno-Eguilaz ◽  
Rafael Ruiz-Mansilla ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5122
Author(s):  
Bianca Caiazzo ◽  
Angelo Coppola ◽  
Alberto Petrillo ◽  
Stefania Santini

This paper addresses the leader tracking problem for a platoon of heterogeneous autonomous connected fully electric vehicles where the selection of the inter-vehicle distance between adjacent vehicles plays a crucial role in energy consumption reduction. In this framework, we focused on the design of a cooperative driving control strategy able to let electric vehicles move as a convoy while keeping a variable energy-oriented inter-vehicle distance between adjacent vehicles which, depending on the driving situation, was reduced as much as possible to guarantee air-drag reduction, energy saving and collision avoidance. To this aim, by exploiting a distance-dependent air drag coefficient formulation, we propose a novel distributed nonlinear model predictive control (DNMPC) where the cost function was designed to ensure leader tracking performances, as well as to optimise the inter-vehicle distance with the aim of reducing energy consumption. Extensive simulation analyses, involving a comparative analysis with respect to the classical constant time headway (CTH) spacing policy, were performed to confirm the capability of the DNMPC in guaranteeing energy saving.


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