Optimization of Harvester System in embedded vehicle systems via Bond Graph modeling algorithm

Touairi, Souad; Mabrouki, Mustapha

doi:10.1109/icoa49421.2020.9094463

Cited by 8 publications

(2 citation statements)

References 10 publications

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“…For this issue, road roughness is considered as a small value at high frequency, whereas a hill is considered a larger value at the low frequency of road discomfort [37]. Vibratory energy recovery is aimed then at realizing microelectrical generators of centimetric size allowing electronic system feed by absorbing the "ambient" energy present in the surrounding environment [38][39][40]. Typically, the vehicle's suspension system consists of a spring and dampers-which are used for the vehicle's adaptive oscillation, linking the vehicle to its wheels [41].…”

Section: Introductionmentioning

confidence: 99%

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Touairi,

Zekraoui,

Mabrouki

2024

Modelling and Simulation in Engineering

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The present investigation introduces an advanced methodology for maximum power point tracking (MPPT) applied to a piezo harvester scheme. A comprehensive rectifier circuit, equipped with an embedded MPPT component, is established to optimize energy production by monitoring a DC-DC inverter connected to the rectifier. Furthermore, the system’s sensitivity error has been finely tuned to dynamically adjust its impedance unit in real time, thereby optimizing load acquisition. This innovative approach seamlessly integrates the MPPT algorithm into the piezo harvester circuit. Moreover, the vehicle’s road handling is significantly augmented through the incorporation of a robust steering front and an active differential control system. Leveraging the MPPT module, the rectifier consistently achieves a power recovery efficiency exceeding 85%, independent of varying load conditions. Additionally, a DC-DC converter circuit has been seamlessly integrated to finely adjust the output voltage to meet specified levels. Numerical simulations demonstrate the effectiveness of the harvesting scheme, extracting a substantial output power of 90 W with an overall efficiency of 70%. The improved MPPT approach, employing angles of arrival (AoA) DV-Hop control strategies, minimizes the system’s power consumption based on the Global Positioning System (GPS). The utilization of Harris Hawks optimization (HHO) and the generation of quadrants in the four-quadrant operation mode of DC motors in the wireless sensor network (RCSFs) have been significantly enhanced in this study. Simulations reveal that, at a velocity of 50 km/h, shock absorbers utilizing the received signal strength indication (RSSI) can harvest between 60 and 90 W on a class C road, based on the time of arrival (TOA). Striking a balance in ride comfort using the time difference of arrival (TDOA) as a trade-off constitutes approximately 30% of the piezoelectric harvester (PEH) system’s power consumption when operating in active suspension mode, optimized by particle swarm optimization (PSO).

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Section: Introductionmentioning

confidence: 99%

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Touairi,

Zekraoui,

Mabrouki

2024

Modelling and Simulation in Engineering

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“…On the other side, there are many popular techniques that have been applied and realized to collect various vibration energies carry out on the vehicle body. This external excitation can change the vehicle's engine behaviour or the car's antilock brakes device (ABD) [19]. The authors of [20], [21] have been proposed an applicable strategy to collect high bandwidth of vibrations energy through the use of transducer attached to the suspension system.…”

Section: Introductionmentioning

confidence: 99%

Vibration harvesting integrated into vehicle suspension and bodywork

Touairi

Mabrouki

2021

IJEECS

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This work proposes a new piezoelectric transducer system with four freedoms of movement modelled and evaluated by mechatronic techniques. The proposed modelling techniques (finite element and bond graph) were performed in a 20-Sim framework attached to the ANSYS software. The established harvester system has the ability to increase the driver's comfort when travelling on several types of road surfaces. The piezoelectric harvester is designed to investigate and provide the health requirement and ride comfort of the vehicle's drives on random road surfaces. The simulation results affirm that the improved piezoelectric transducer arrangement is more productive for various aspects. The power recovery is significantly enhanced as well as the driving comfort on the three road categories. Finally, the harvestable power amount is highlighted and is graphically discussed for several specific applications.

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Improve the Energy Harvesting Alternatives Using the Bond Graph Approach for Powering Critical Autonomous Devices

Touairi

Mabrouki

2021

Digital Technologies and Applications

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Optimization of Harvester System in embedded vehicle systems via Bond Graph modeling algorithm

Cited by 8 publications

References 10 publications

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Vibration harvesting integrated into vehicle suspension and bodywork

Improve the Energy Harvesting Alternatives Using the Bond Graph Approach for Powering Critical Autonomous Devices

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