Maximum Power Point Tracking Control of a Thermoelectric Generation System Using the Extremum Seeking Control Method

Twaha, Ssennoga; Zhu, Jun; Maraaba, Luqman S.; Huang, Kai‐Fa; Li, Bo; Yan, Yuying

doi:10.3390/en10122016

Cited by 10 publications

(4 citation statements)

References 37 publications

(40 reference statements)

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“…In addition to the effects of the structural design, improvements in ATEG performance can also be obtained by adopting state-of-the-art electronic techniques to maximize power generation in transient behaviors (e.g., maximum power point tracking control [46]). Finally, the ongoing research into new thermoelectric materials is expected to substantially increase the actual values of figure of merit in commercial modules in future years [47,48].…”

Section: Configurations With Maximum Power and Maximum Fuel Economymentioning

confidence: 99%

Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator

Comamala

Cózar

Massaguer³

et al. 2018

Energies

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The need for more sustainable mobility promoted research into the use of waste heat to reduce emissions and fuel consumption. As such, thermoelectric generation is a promising technique thanks to its robustness and simplicity. Automotive thermoelectric generators (ATEGs) are installed in the tailpipe and convert heat directly into electricity. Previous works on ATEGs mainly focused on extracting the maximum amount of electrical power. However, the back pressure caused by the ATEG heavily influences fuel consumption. Here, an ATEG numerical model was first validated with experimental data and then applied to investigate the effects that modifying the main ATEG design parameters had on both fuel economy and output power. The cooling flow rate and the geometrical dimensions of the heat exchanger on the hot side and the cold side of the ATEG were varied. The design that produced the maximum output power differed from that which maximized fuel economy. Back pressure was the most limiting factor in attaining fuel savings. Back pressure values lower than 5 mbar led to a < 0.2% increase in fuel consumption. In the ATEG design analyzed here, the generation of electrical output power reduced fuel consumption by a maximum of 0.5%.

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Section: Configurations With Maximum Power and Maximum Fuel Economymentioning

confidence: 99%

Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator

Comamala

Cózar

Massaguer³

et al. 2018

Energies

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show abstract

“…Energy converters, such as the one proposed, efficiently compensate for load disturbances when in the energy conservation mode. The authors of [9] proposed and considered an extremum seeking control (ESC) algorithm-based MPPT approach for a TEG converter. The efficiency of the ESC method has been compared with the P&O method under the same circumstances; the demonstrative results report that the ESC-based MPPT approach captured more energy than the P&O-based one.…”

Section: Introductionmentioning

confidence: 99%

A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System

2021

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Thermoelectric generators (TEGs) are equipment for transforming thermal power into electricity via the Seebeck effect. These modules have gained increasing interest in research fields related to sustainable energy. The harvested energy is mostly reliant on the differential temperature between the hot and cold areas of the TEGs. Hence, a reliable maximum power point tracker is necessary to operate TEGs too close to their maximum power point (MPP) under an operational and climate variation. In this paper, an optimized fractional incremental resistance tracker (OF-INRT) is suggested to enhance the output performance of a TEG. The introduced tracker is based on the fractional-order PIλDμ control concepts. The optimal parameters of the OF-INRT are determined using a population-based sine cosine algorithm (SCA). To confirm the optimality of the introduced SCA, experiments were conducted and the results compared with those of particle swarm optimization- (PSO) and whale optimization algorithm (WOA) -based techniques. The key goal of the suggested OF-INRT is to overcome the two main issues in conventional trackers, i.e., the slow dynamics of traditional incremental resistance trackers (INRT) and the high steady-state fluctuation around the MPP in the prevalent perturb and observe trackers (POTs). The main findings prove the superiority of the OF-INRT in comparison with the INRT and POT, for both dynamic and steady-state responses.

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“…e advantage is they do not consider the complexity of the model, and logic is simple [7], but the disadvantage is that it will cause multiple disturbances of the circuit, the control speed is slow, and the adjustment cannot be realized in one step [8]. e improved disturbance observation method can improve the tracking speed by a reasonable adaptive step size control strategy, such as changing the disturbance step size according to the slope of the P-U curve, and can alleviate the oscillation of the circuit at the maximum power point [9]. e traditional centralized inverter utilizes a master MPPT controller to control the total output power of the photovoltaic power station by disturbance observation [10].…”

Section: Introductionmentioning

confidence: 99%

Vehicle‐Mounted Photovoltaic System Energy Management in Intelligent Transportation Systems: A Maximum Power Point Tracking Control

2021

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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.

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Maximum Power Point Tracking Control of a Thermoelectric Generation System Using the Extremum Seeking Control Method

Cited by 10 publications

References 37 publications

Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator

Effects of Design Parameters on Fuel Economy and Output Power in an Automotive Thermoelectric Generator

A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System

Vehicle‐Mounted Photovoltaic System Energy Management in Intelligent Transportation Systems: A Maximum Power Point Tracking Control

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