Intelligent Energy Management System for Mobile Robot

Abstract

Mobile robots used for search and rescue suffer from uncertain time duration for sustainable operation. Solar energy has the drawback that it fluctuates depending on the weather. By integrating the battery and supercapacitor, the energy management system eliminates this shortcoming. Managing power sharing between the battery and the supercapacitor is conducted by the fuzzy logic controller and proportional integral controller. The fuzzy logic controller provides a reference value to the proportional integral controller to keep the supercapacitor voltage at a certain value. It provides sufficient space to store solar energy and at the same time helps the battery to stay longer for operation. Moreover, the proposed energy management system offers a feature for providing a load power reference recommendation and offers the hibernate mode to save energy when the main power source is too weak, and it is suitable for mobile robot application. The simulation and experiment show that the energy management system design maintains the supercapacitor voltage and regulates the power sharing. Moreover, it also provides a percentage power reference recommendation for the central controller to manage its load current. It reduces the battery power consumption up to 35% and reduces peak current up to 5%, depending on the existing photovoltaic current and load management.

A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing

“…Figure 8 illustrates the comprehensive fuzzy inference process, encompassing (1) input variables' fuzzification, (2) antecedent's AND, OR, and NOT operators' application, (3) consequent's implication operator application (IF-THEN), (4) all rules' consequents aggregation, and (5) output variable defuzzification. Fuzzy logic's versatility spans various domains, including control systems like process temperature regulation [69], energy management [70,71], vacuum cleaning [72], automatic transmission [73], washing machines [74], and pattern recognition tasks such as gait [75], speckle [76], and behavior [77] pattern analysis. In image processing, it aids in image enhancement [78,79], segmentation [80,81], and registration [82]).…”

“…Table 2 delineates these variables across industries and processes. Fuzzy logic's versatility spans various domains, including control systems like process temperature regulation [69], energy management [70,71], vacuum cleaning [72], automatic transmission [73], washing machines [74], and pattern recognition tasks such as gait [75], speckle [76], and behavior [77] pattern analysis. In image processing, it aids in image enhancement [78,79], segmentation [80,81], and registration [82]).…”