Battery Recharging Research Articles

Fuzzy Multi-Agent Simulation for Collective Energy Management of Autonomous Industrial Vehicle Fleets

This paper presents a multi-agent simulation implemented in Python, using fuzzy logic to explore collective battery recharge management for autonomous industrial vehicles (AIVs) in an airport environment. This approach offers adaptability and resilience through a distributed system, taking into account variations in AIV battery capacity. Simulation scenarios were based on a proposed charging/discharging model for an AIV battery. The results highlight the effectiveness of adaptive fuzzy multi-agent models in optimizing charging strategies, improving operational efficiency, and reducing energy consumption. Dynamic factors such as workload variations and AIV-infrastructure communication are taken into account in the form of heuristics, underlining the importance of flexible and collaborative approaches in autonomous systems. In particular, an infrastructure capable of optimizing charging according to energy tariffs can significantly reduce consumption during peak hours, highlighting the importance of such strategies in dynamic environments. An optimal control model is established to improve the energy consumption of each AIV during its mission. The energy consumption depends on the speed, as demonstrated via numerical simulations using realistic data. The speed profile of each AIV is adjusted according to the various constraints within an airport. Overall, the study highlights the potential of incorporating adaptive fuzzy multi-agent models for AIV energy management to boost efficiency and sustainability in industrial operations.

Management and monitoring of lithium-ion battery recharge with ESP32

Management and monitoring of lithium-ion battery recharge with ESP32

Implementation of Regenerative Brake System Controller by Using Mini Controller Arduino

The key requirement for electric vehicles is efficient braking. The objective of this study is to provide a detailed description of the regenerative braking system utilizing various power flow regulators. This study utilizes a buck-boost type Boost Converter. There are two methods employed to modify the voltage derived from the fluctuating input produced during regenerative braking: one to decrease it and the other to boost it. Subsequently, a voltage sensor detects the resulting output voltage, which is then regulated using an Arduino microcontroller. The examination findings indicate that the buck-boost converter performs well, maintaining an output voltage within the range of 39-40 volts. This allows it to function well even when there are fluctuations in the input voltage. The voltage value can be utilized for the purpose of charging a battery for a 36 Volt electric motor. The findings demonstrate the efficacy of utilizing a Buck-Boost Converter regulator. Furthermore, it could charge the battery within a span of 8 seconds, making it a viable option for electric vehicles as an alternative to regenerative braking for battery recharging.

Municipal solid waste management using electric vehicle by variable neighbourhood search algorithm

Efficient solid waste management is essential for addressing the multifaceted challenges associated with waste disposal, including environmental, economic, technical, and social aspects. Municipal solid waste management (MSWM) incurs significant costs and contributes to environmental pollution primarily due to the collection process. This research presents a comprehensive case study that focuses on optimising the routing of electric vehicles for solid waste collection. Specifically, it addresses the Half-Open Time-Dependent Multi-Depot Electric Vehicle Routing Problem considering Battery Recharging and Swapping (HOTDMDEVRPBRS) in the context of waste collection. This problem aims to optimise the routes taken by electric vehicles across multiple depots, considering constraints such as limited battery capacity, multiple technologies for recharging battery capacity, the impact of truckload on energy consumption, and time-dependent travel times. To tackle this problem, we propose a highly efficient Variable Neighborhood Search (VNS) meta-heuristic algorithm, which outperforms the Simulated Annealing (SA) approach. The proposed algorithm achieves an average improvement of 11.88% in solution quality and reduces execution time by 73% for last-mile delivery. We evaluate the effectiveness of the proposed approach using real-world data from New York's recycling management system. The findings of this study emphasise the potential for enhancing solution quality and operational efficiency in solid waste management.

Dynamic pickup and delivery problem for autonomous delivery robots in an airport terminal

Autonomous delivery robot (ADR) operation for short-range delivery purposes is becoming an increasingly popular mode of service. Assigning orders to robots is critical in ensuring high quality in these automated delivery operations. This paper considers a dynamic pickup and delivery problem using autonomous robots (DPDP-AR), where a fleet of ADRs picks up desired items from stores and delivers them to customers. The arrival time of orders is uncertain, with a hard delivery deadline for each order. This study considered the battery consumption of ADRs, which has been less extensively covered in previous research, and devised a battery recharging strategy for the operation. To handle this stochasticity and dynamism in the problem, we developed a reassignment algorithm that reschedules previously assigned orders at the arrival of a new order. Additionally, as periods of high demand can be estimated, peak time management of the battery is proposed to enhance ADR utilization at peak periods. Computational experiments were performed on real-world ADR food delivery service instances in an airport terminal. Test instances on various demand scenarios demonstrated improvement in service quality when devised policies were used compared to current practice. We substantiated that the proposed algorithms found efficient solutions within short computation times, validating their applicability to real-world operations.

High‐Performance Hematite Photoanodes for Unassisted Recharging of Solar Redox Flow Battery

Solar redox flow batteries (SRFB) have attracted increasing interest for simultaneous capture and storage of solar energy by integrating a photoelectrochemical cell with a redox flow battery. Herein, a scalable, nanostructured α‐Fe2O3 photoanode exhibiting a high photovoltage of 0.68 V in a fully integrated Na4Fe(CN)6/AQDS SRFB is demonstrated. Thanks to its optimal band alignment, it uniquely enables stable, unassisted photocharging of the SRFB up to a state‐of‐charge (SOC) higher than 50%. Concurrently, its improved charge transfer results in a record unbiased photocurrent density of 0.22 mA cm−2, with a sixfold increase at zero SOC compared to α‐Fe2O3 film. Through an in‐depth optical and photoelectrochemical characterization of different α‐Fe2O3 morphologies, the impact of nanostructuring on charge transfer is quantified. Most interestingly, an increase in unbiased photocurrent is observed at 10% SOC (0.31 mA cm−2) and attributed to adsorption of ferricyanide, which enhances charge transfer. Importantly, it is demonstrated that the superior performance is retained after device scale‐up to 5.72 cm2. Overall, the demonstrated unassisted device is on par with previously reported dye‐sensitized solar cell‐assisted hematite‐based SRFBs. More broadly, this work contributes to the real‐world deployment of cost‐effective SRFBs based on Earth‐abundant materials.

A model-based approach for formal verification and performance evaluation of energy harvesting architectures in IoT systems: A case study of a long-term healthcare application

Energy harvesting plays a significant role in the Internet of Things (IoT). Indeed, although numerous approaches exist to limit the system’s power consumption, the energy provided by the battery remains constrained, thereby limiting the system’s lifetime. Energy harvesting represents an interesting technique that allows a set of devices in an IoT architecture to operate for a potentially infinite time without the need for battery replacement or recharge. This work presents a formal modeling framework for the performance evaluation of energy harvesting architectures and strategies in IoT systems. We present a model-based approach using UPPAAL to model and analyze IoT device lifetimes and capture the energy-related behavior of nodes and various energy harvesters. Furthermore, the model is calibrated using measurements acquired from real-life IoT applications to demonstrate the effectiveness of the proposed model and its ability to investigate various energy-related aspects.

Demonstrating the feasibility of monitoring bone fracture healing using electromechanical impedance spectroscopy – a comparison between three different inputs in Ward’s hierarchical clustering method

Current methods for monitoring the progression of bone fracture healing require large, complex, and expensive imaging technology and, if used repeatedly, can expose patients to harmful ionizing radiation. Recent development of miniaturized, implantable, inexpensive microelectronic sensing technology now makes it possible to continuously monitor fracture healing non-invasively at the patient's bedside. This proof-of-concept study demonstrates a novel, smart, implantable medical device based on electromechanical impedance spectroscopy. The setup consists mainly of a piezoceramic disk (PIC255 from PI Ceramics), an impedance chip (AD5933 from Analog Devices) and an inductive battery recharging system. The system operates autonomously for 24 hours of measurements. Every 20 minutes, the health state of the bone is measured. To test the setup, 20 tibia bones of sheep limbs obtained from a butcher's shop are used. By drilling five holes into the bone one after another, different defects mimicking bone fractures of different sizes are created. This simulates an inverse bone healing process. The collected data is transmitted via Bluetooth LE to a portable device that displays the impedance spectra. After the results have been reviewed, the data is transferred to a computer for statistical evaluation, such as the Root Mean Square Deviation (RMSD). Preliminary results have shown an increasing trend in RMSD with increasing number of holes in the bone. Based on these observations, an in-vivo study is planned.

Hybrid Power Source Assisted by Renewable Energies for Hybrid Electric Vehicles

The article studies and analyzes a hybrid power source system, lithium battery, and fuel cell assisted by flexible photovoltaic panels for hybrid electric vehicles (HEVs). The new configuration operates based on optimizing the performance of the dual power source to maximize the available energy and operating time. The operational mode simulates specific driving conditions in urban, peripheral, and intercity routes under variable driving patterns and traffic conditions. The simulation results show that the new configuration increases the hybrid electric vehicle performance, providing higher reliability despite the more complex design. The proposed system reduces the external power supply dependence and avoids unexpected sudden stops due to energy exhaustion. The new configuration also extends the vehicle driving range depending on driving mode and route conditions. The vehicle driving range extension may reach up to 276.3 km. The hybridization of fuel cells with lithium battery and PV panel assistance enhances battery management, reducing battery servicing and increasing lifespan. The proposed topology is cheaper than a single fuel cell power system by 17.2%, reducing the total cost related to the single battery power system if we consider the battery recharge for its entire lifespan. The cost saving is 2.6% for the American market and 14.8% for the European one.

Secondary cluster head based SEP in heterogeneous WSNs for IoT applications

AbstractA wireless sensor network (WSN) consists of specialized sensor nodes that perform sensing services for Internet of Things devices with limited battery power. As the replacement or recharging of batteries is not possible, energy consumption becomes the most important design issue in WSNs. The energy‐efficient routing protocol gets the most priority in such energy‐constrained networks. The utilization of clustering‐based routing protocols like stable election protocol (SEP) has gained much attention as the network's lifetime is significantly improved due to the clustering of sensor nodes. Moreover, the inclusion of a secondary CH (SCH) is beneficial when the member node with the most remaining energy performs data aggregation and reduces the energy burden of the CH. This article characterizes SEP and Prolong SEP (P‐SEP) protocols and then extends them by incorporating SCH, which ensures balanced energy consumption. The performance of the proposed Extended SEP and Extended P‐SEP protocols has been analysed regarding stability period, network lifetime, energy usage and throughput. The simulation results demonstrate that the proposed protocols outperform state‐of‐the‐art protocols like P‐SEP, Modified SEP (M‐SEP) and SEP. In particular, the stability period of Extended SEP and Extended P‐SEP has improved up to 42% and 89%, respectively, compared to M‐SEP.

Energy Consumption Optimization based on Economic Benefit in WSN-based IoT via Global Hierarchical Caching Strategy

Recent advances in Wireless Sensor Network (WSN) have significantly contributed to the prevalence of Internet of Things (IoT) devices and their pervasive integration into everyday life and industrial operations. A WSN-based IoT comprises numerous small, scattered, battery-operated sensors that are designed to perform collaborative tasks. These sensor nodes are prone to energy drain because of their limited battery capacity when they needed to run efficiently over extended periods of time. Enhancing the large-scale network’s lifespan and controlling the economic costs become relevant since battery replacement or recharging is impractical in severe environments. In this paper, we present a novel energy optimization algorithm tailored for WSNs, which not only takes into account the reduction in replacement costs stemming from prolonged equipment lifespan but also incorporates the operational savings resulting from enhanced energy efficiency. It aims to enhance energy efficiency by leveraging a global hierarchical caching mechanism to simultaneously balance exploration and exploitation of energy resources in both the uplink and downlink of the networks. The simulation results demonstrate that our algorithm effectively minimizes energy consumption while maintaining optimal economic efficiency by decreasing the frequency of state transitions. It can consume 13% less energy than original system and extend the network lifetime by 10%.

BIM based on energy & cost analysis in response to the day light intensity of a building

Construction of building with proper auditing of energy is one of the challenges faced in the AEC (Architecture Engineering and Construction) industries. The need of opt sources of energy affordability in the building lights can reduce the consumption of electricity and cut down the cost of bills. The trending application in using building information modelling (BIM) for the energy saving concept on daylight factors in various building like government office, commercial complex, school building and office building are significant to achieve the sustainability goals on sustainable cities and communities, responsible consumption and production including life on land. For the present studies, perspective BIM model is developed for the G+1 residential building covering the plot area of 1,815 square feet located in Phagwara, India. The building plan is prepared considering the sunlight orientation to configure the maximum daylight and ventilation are provided for the building as per the prevailing wind direction towards North-East latitude and longitude of 31° 13’ 26.4720’' N and 75° 46’ 14.8728’' E respectively. On the aspect of saving energy, the solar panel idea is added over the roof top, which can be utilized for the electric geysers and garden lighting, excess energy is used for the recharging of inverter batteries of the house. The energy model is audited with conventional building, it is understood the annual energy consumption has decreased to 36.9 k Wh/m2/ year as per the Punjab state electric board. Building Energy Simulation (BES) and Life Cycle Assessment (LCA) data is collected as per the location of the building, further the details are used for the modelling by using the Autodesk Revit and Autodesk Insight. Energy Used Intensity identified as less than 14.6 kWh/m2/year is needed to meet the Passive House criteria as per the studies, which can reduce the daylight effect on energy consumption. Therefore, it is understood, by the application of BIM is adding the virtual importance and elicit awe in the civil engineering domain.

Quasi-Solid Sulfur Conversion for Energetic All-Solid-State Na-S Battery.

The high theoretical energy density (1274 Wh kg-1) and high safety enable the all-solid-state Na-S batteries with great promise for stationary energy storage system. However, the uncontrollable solid-liquid-solid multiphase conversion and its associated sluggish polysulfides redox kinetics pose a great challenge in tunning the sulfur speciation pathway for practical Na-S electrochemistry. Herein, we propose a new design methodology for matrix featuring separated bi-catalytic sites that control the multi-step polysulfide transformation in tandem and direct quasi-solid reversible sulfur conversion during battery cycling. It is revealed that the N, P heteroatom hotspots are more favorable for catalyzing the long-chain polysulfides reduction, while PtNi nanocrystals manipulate the direct and full Na2S4 to Na2S low-kinetic conversion during discharging. The electrodeposited Na2S on strongly coupled PtNi and N, P-codoped carbon host is extremely electroreactive and can be readily recovered back to S8 without passivation of active species during battery recharging, which delivers a true tandem electrocatalytic quasi-solid sulfur conversion mechanism. Accordingly, stable cycling of the all-solid-state soft-package Na-S pouch cells with an attractive specific capacity of 876 mAh gS -1 and a high energy of 608 Wh kgcathode -1 (172 Wh kg-1, based on the total mass of cathode and anode) at 60 °C are demonstrated.

Hydrogen for Mobility: A Pathway to a Zero Carbon Transportation System

Eliminating hydrocarbon transportation must be a fundamental goal for society if we are to negate Climate Change and its consequences. No source of CO2 emissions comes close to that of hydrocarbon fueled internal combustion engines and if we are to transition to a zero-carbon energy system, a viable alternative to hydrocarbon fuels must be found. Lithium-Ion powered vehicles or EV’s present society with a paradox, they emit zero emissions however the life cycle of Lithium-Ion batteries is a source of environmental concern through mining, deforestation of carbon sinks, the immense electrification requirements for battery production, recycling, and recharging. This communication proposes Hydrogen for Mobility as the future fuel for a pathway to a Zero Carbon Transportation System through utilizing both the existing internal combustion engine (ICE) and most existing transportation infrastructure, at the same time being cost effective, efficient and zero emitting. An overview of technologies will be discussed along with their Technology Readiness, benefits, and issues. This discussion expands on the concepts discussed in ‘Mobile Modular Hydrogen Power Generation – a Zero Carbon Energy System’. https://doi.org/10.5296/ijgs.v7i1.xxxx

Wireless and Catheter-Free Bladder Pressure and Volume Sensor.

Continuous monitoring of bladder activity during normal daily activities would improve clinical diagnostics and understanding of the mechanisms underlying bladder function, or help validate how differing neuromodulation strategies affect the bladder. This work describes a urological monitor of conscious activity (UroMOCA). The UroMOCA included a pressure sensor, urine impedance-sensing electrodes, and wireless battery recharge and data transmission circuitry. Components were assembled on a circuit board and encapsulated with an epoxy/silicone molded package that allowed Pt-Ir electrode feedthrough for urine contact. Packaged UroMOCAs measured 12 × 18 × 6 mm. UroMOCAs continuously transmitted data from all onboard sensors at 10 Hz at 30 cm range, and ran for up to 44 hours between wireless recharges. After in vitro calibration, implantations were performed in 11 animals. Animals carried the device for 28 days, enabling many observations of bladder behavior during natural, conscious behavior. In vivo testing confirmed the UroMOCA did not impact bladder function after a two-week healing period. Pressure data in vivo were highly correlated to a reference catheter used during an anesthetized follow-up. Static volume sensor data were less accurate, but demonstrated reliable detection of bladder volume decreases, and distinguished between voiding and non-voiding bladder events.

Quasi‐Solid Sulfur Conversion for Energetic All‐Solid‐State Na−S Battery

AbstractThe high theoretical energy density (1274 Wh kg−1) and high safety enable the all‐solid‐state Na−S batteries with great promise for stationary energy storage system. However, the uncontrollable solid–liquid‐solid multiphase conversion and its associated sluggish polysulfides redox kinetics pose a great challenge in tunning the sulfur speciation pathway for practical Na−S electrochemistry. Herein, we propose a new design methodology for matrix featuring separated bi‐catalytic sites that control the multi‐step polysulfide transformation in tandem and direct quasi‐solid reversible sulfur conversion during battery cycling. It is revealed that the N, P heteroatom hotspots are more favorable for catalyzing the long‐chain polysulfides reduction, while PtNi nanocrystals manipulate the direct and full Na2S4 to Na2S low‐kinetic conversion during discharging. The electrodeposited Na2S on strongly coupled PtNi and N, P‐codoped carbon host is extremely electroreactive and can be readily recovered back to S8 without passivation of active species during battery recharging, which delivers a true tandem electrocatalytic quasi‐solid sulfur conversion mechanism. Accordingly, stable cycling of the all‐solid‐state soft‐package Na−S pouch cells with an attractive specific capacity of 876 mAh gS−1 and a high energy of 608 Wh kgcathode−1 (172 Wh kg−1, based on the total mass of cathode and anode) at 60 °C are demonstrated.

Green IoT Based on Tropical Weather: The Impact of Energy Harvesting in Wireless Sensor Network

Wireless Sensor Networks (WSNs) are a key component of Green IoT, as they play a critical role in many applications. However, a major challenge faced by WSNs is their limited energy capacity, which can impede their effectiveness. To address this issue, energy harvesting techniques are used to harness ambient energy and power the nodes, eliminating the need for frequent battery replacements or recharging. This study proposes a solar energy harvesting technique to prolong the lifespan of each wireless sensor node in a network. The aim of the research is to assess the impact of energy harvesting on wireless sensor networks with a focus on solar ambient light energy, as it is a critical component of achieving a Green Internet of Things (IoT). The study is adapted to the tropical weather of Malaysia and its forecasted conditions. Through the use of NetSim simulations, the energy efficiency and reliability of the network are evaluated using solar energy harvesting. The recharge rate for energy harvesting in a wireless sensor network is calculated to be 2.34W per day using a 55x70mm solar photovoltaic panel based on Malaysia weather forecasts and sun hours. This proposed method is successfully executed using NetSim, which utilizes real device parameters for a WSN in a simulated agriculture environment. The results show an overall improvement of 22.4 percent in performance parameters in all areas, including energy consumption, network layer, routing performance, and IEEE 802.15.4 metrics, representing a significant improvement. With the implementation of solar energy harvesting, traditional energy of WSNs can benefit from developing smart agricultural monitoring systems. This efficient method and calculation for solar energy harvesting can help to sustain the infinite lifetime of WSN by optimizing the operational time to 18% of the duty cycle. Results demonstrate that the proposed method can effectively increase the energy efficiency and reliability of the network, making it a promising solution for WSNs operating in tropical regions. This research contributes to the development of sustainable and energy-efficient WSNs, promoting the Green IoT concept.

Design and Construction of Radio-Controlled Glider with Renewable Energy Capabilities

Thermal columns are a meteorological phenomenon which is frequently used by birds to rise without requiring wing power. Imitating this behaviour with an aircraft can utilize this lift to provide energy for the electrical components of the system. In this study, a radio-controlled glider with a built-in wind turbine and generator was designed and constructed. The generator is intended to provide renewable energy during glides, especially when thermal columns are harnessed. The glider was constructed using composite materials, which combine a high level of strength together with light-weight, improving energy efficiency. Turbine design was implemented using a duct-fan model which increases air flow to the generator. Test flight measurements indicate efficient battery recharging can be obtained during glides. The system may be implemented in manned or unmanned gliders, for agricultural, civil, or security uses, such as unmanned surveillance airplanes.

Binary Atomic Sites Enable a Confined Bidirectional Tandem Electrocatalytic Sulfur Conversion for Low-Temperature All-Solid-State Na-S Batteries.

The broader implementation of current all-solid-state Na-S batteries is still plagued by high operation temperature and inefficient sulfur utilization. And the uncontrollable sulfur speciation pathway along with the sluggish polysulfide redox kinetics further compromise the theoretical potentials of Na-S chemistry. Herein, we report a confined bidirectional tandem electrocatalysis effect to tune polysulfide electrochemistry in a novel low-temperature (80 °C) all-solid-state Na-S battery that utilizes Na3 Zr2 Si2 PO12 ceramic membrane as a platform. The bifunctional hollow sulfur matrix consisting binary atomically dispersed MnN4 and CoN4 hotspots was fabricated using a sacrificial template process. Upon discharge, CoN4 sites activate sulfur species and catalyze long-chain to short-chain polysulfides reduction, while MnN4 centers substantially accelerate the low-kinetic Na2 S4 to Na2 S directly conversion, manipulating the uniform deposition of electroactive Na2 S and avoiding the formation of irreversible products (e.g., Na2 S2 ). The intrinsic synergy of two catalytic centers benefits the Na2 S decomposition and minimizes its activation barrier during battery recharging and then efficiently mitigate the cathodic passivation. As a result, the stable cycling of all-solid-state Na-S cell delivers an attractive reversible capacity of 1060 mAh g-1 with a high CE of 98.5 % and a high energy of 1008 Wh kgcathode -1 , comparable to the liquid electrolyte cells.

Binary Atomic Sites Enable a Confined Bidirectional Tandem Electrocatalytic Sulfur Conversion for Low‐Temperature All‐Solid‐State Na−S Batteries

AbstractThe broader implementation of current all‐solid‐state Na−S batteries is still plagued by high operation temperature and inefficient sulfur utilization. And the uncontrollable sulfur speciation pathway along with the sluggish polysulfide redox kinetics further compromise the theoretical potentials of Na−S chemistry. Herein, we report a confined bidirectional tandem electrocatalysis effect to tune polysulfide electrochemistry in a novel low‐temperature (80 °C) all‐solid‐state Na−S battery that utilizes Na3Zr2Si2PO12 ceramic membrane as a platform. The bifunctional hollow sulfur matrix consisting binary atomically dispersed MnN4 and CoN4 hotspots was fabricated using a sacrificial template process. Upon discharge, CoN4 sites activate sulfur species and catalyze long‐chain to short‐chain polysulfides reduction, while MnN4 centers substantially accelerate the low‐kinetic Na2S4 to Na2S directly conversion, manipulating the uniform deposition of electroactive Na2S and avoiding the formation of irreversible products (e.g., Na2S2). The intrinsic synergy of two catalytic centers benefits the Na2S decomposition and minimizes its activation barrier during battery recharging and then efficiently mitigate the cathodic passivation. As a result, the stable cycling of all‐solid‐state Na−S cell delivers an attractive reversible capacity of 1060 mAh g−1 with a high CE of 98.5 % and a high energy of 1008 Wh kgcathode−1, comparable to the liquid electrolyte cells.