Vehicle-Mounted Photovoltaic System Energy Management in Intelligent Transportation Systems: A Maximum Power Point Tracking Control. (5th August 2021)

• Record Type: Journal Article
• Authors: Wang, Jingao; Liu, Qifei; Jing, Silan
• Other Names: Selisteanu Dan Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-08-05
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/5578972
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Electric vehicles have become the main contributor in terms of reducing fuel consumption and CO2 emission. Although the government is vigorously promoting the use of electric vehicles worldwide, the range anxiety still impedes the rapid development of electric vehicles, especially when air-conditioning also adds battery power consumption and aggravates the range anxiety. To this end, this paper proposes an improved vehicle-mounted photovoltaic system energy management in intelligent transportation systems, which is a maximum power point tracking control system. Meanwhile, since the power of solar panels is usually relatively small and the power changes at any time, low power density and poor controllability are difficult to avoid. In order to solve this problem, this paper offers a tracking control method to improve the output efficiency of solar panels. For improving photovoltaic conversion efficiency and maximizing output power, traditional photovoltaic power panels are often dominated by a centralized maximum power point tracing control, which is named MPPT. Although the cost under this case is lower, the output power of all photovoltaic panels cannot be maximized under the condition of uneven illumination or local mismatch. To improve the situation, a micro-scale inverter is proposed to provide MPPT control of photovoltaic modules, which can effectively improve the output power of each photovoltaic panel. Moreover, our MPPT algorithm is applicable to cloud shadow, building shadow, and shade, and it is more suitable for the car roof. Firstly, the Diode 5-parameter model is used to deduce the I - U equation of the photovoltaic module considering shadow shading, and then the real-time 5 parameter equation is formed by using the measured data group and selected. The reasonable initial value is used to iteratively solve the real-time value of 5 parameters, which is further to judge the masking situation. The maximum power point (MPP) is solved directly by the mathematical method based on the mathematical model of I - U relation mathematics, and the DC-DC circuit is used to adjust the running point to MPP. Unlike the traditional MPPT method, the method in this paper is based on the physical model of solar cells, and MPP tracking is based on mathematical methods. Based on this, it does not need to cause multiple interference to the circuit, and the tracking efficiency is high. Finally, the relative experimental results are provided to verify the performance of the proposed method.