Real-time range estimation in electric vehicles using fuzzy logic classifier

2020 ◽  
Vol 83 ◽  
pp. 106577 ◽  
Author(s):  
Süleyman Çeven ◽  
Ahmet Albayrak ◽  
Raif Bayır
Author(s):  
Feng Liu

The disorderly charging of large-scale electric vehicles will aggravate the peak-valley difference of the power grid, and affect the power quality and life of the transformer. The fuzzy logic control strategy for charging and discharging optimization of charging vehicles under the framework of fuzzy logic control from the perspective of the group is considered in this article. A real-time control method based on the clustering characteristics of the charging end time is proposed according to the different charging requirements of the connected electric vehicles and fuzzy logic control is adopted to solve the problem of optimal charging and discharging power of the entire cluster and a single electric vehicle. A fuzzy logic control model considering the charging and discharging of electric vehicles is established orienting at minimize daily load fluctuations and control penalties in the upper layer. The charging and discharging cost of electric vehicle owners is considered to solve the optimal control problem of the charging and discharging power of a single electric vehicle. Taking the data of the typical regional distribution network load as an example, it is verified that the real-time charging optimization strategy under fuzzy logic control through simulation can ensure the reliable operation of the power grid while considering the interests of all parties.


2017 ◽  
Vol 53 (3) ◽  
pp. 1751-1760 ◽  
Author(s):  
Kaveh Sarrafan ◽  
Kashem M. Muttaqi ◽  
Danny Sutanto ◽  
Graham E. Town

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.


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