Battery Replacement Research Articles

Economic Competitiveness of Battery Electric Vehicles vs Internal Combustion Engine Vehicles in India: A Case Study for Two- and Four-Wheelers

<div>The initial cost of battery electric vehicles (BEVs) is higher than internal combustion engine-powered vehicles (ICEVs) due to expensive batteries. Various factors affect the total cost of ownership of a vehicle. In India, consumers are concerned with a vehicle’s initial purchase cost and prefer owning an economical vehicle. The higher cost and shorter range of BEVs compared to ICEVs severely limit their penetration in the Indian market. However, government subsidies and incentives support BEVs. The total cost of ownership assessment is used to evaluate the entire cost of a vehicle to find the most economical option among different powertrains. This study compares 2W (two-wheeler) and 4W (four-wheeler) BEV’s cost vis-à-vis equivalent ICEVs in Delhi and Mumbai. The cost analysis assesses the current and future government policies to promote BEVs. Two assumed policies were applied to estimate future scenarios. Annual distance traveled, battery replacement assumptions, and fuel/electricity prices were used for sensitivity analyses. It was found that the total cost of ownership of 2W BEVs in Mumbai and Delhi was lower than the ICEVs, only if heavily supported by government subsidies and incentives. In contrast, with assumed future policies, owning 4W BEVs was costlier, even with government subsidies. This study showed that if a vehicle travels more than the average annual distance traveled, BEVs can be a better option and make sense for niche applications such as taxi fleet operations or ride-hailing services. The current incentives were much more for 4W than 2W, implying a disproportionate allocation of subsidies to the wealthier, who can afford 4W vehicles. The funds required for subsidies, losses in fuel taxes because of lower sales, and tax exemptions offered to BEVs could cost up to ₹146,062 crores (i.e., $19 billion) annually to the Indian government in 2030, which is ~ ₹973 per capita, excluding investments required to build charging infrastructure. Therefore, India needs a targeted subsidy allocation plan, prioritizing 2W, and a phased strategy for an orderly and inclusive transition to a sustainable mobility future.</div> <section> <h2>Graphical Abstract</h2> <figure> <div><img/></div> </figure> </section>

Wireless charging flexible in-situ optical sensing for food monitoring

Food safety is an important public health issue, real-time monitoring and identification of food freshness is essential to ensure food quality and consumer health. This study presents a wireless charging flexible in-situ optical sensing system (FIOS). FIOS integrates visible (VIS)/near-infrared (NIR) spectral sensors, electronic components, and microcontrollers into flexible circuits by flexible electronic technology, and obtains energy through wireless charging to solve the problem of battery replacement and frequent charging of electronic systems. FIOS exhibits excellent flexibility and bendability which can be attached well to the surface of the food for efficient, accurate, non-destructive, and in-situ monitoring. A prediction model between food quality and spectral data was established by chemometrics to achieve accurate prediction of food quality. It can obtain the spectral information of the food in real-time and transmit the data wirelessly to a cloud platform, which enables the visualization of food quality and facilitates quality traceability. FIOS is characterized by simple craft, low cost, and real-time monitoring, and can be widely deployed as an Internet of Things (IoT) node in food transportation, storage, and sales to improve the transparency of food at all stages and ensure the quality and safety of food. The FIOS has the advantages of portable and non-destructive monitoring, which improves the accuracy of food quality monitoring and provides a new technological program in the field of food quality monitoring. It is expected to promote the development of food quality and safety monitoring in the future and provide consumers with a more reliable guarantee of food quality.

Urban Air Mobility Profitability and Operational Sensitivity to Battery and Charging Technology

Designs for electric vertical takeoff and landing (VTOL) aircraft deviate from traditional aircraft designs and include a wide variety of different configurations. Significant uncertainty also exists regarding the status of future battery technology, including energy density and charge rates. This paper presents a simple analytic model to estimate the profitability of an urban air mobility electric VTOL aircraft for a variety of vehicle configurations, battery technology parameters, and economic factors. Five main elements are considered by the framework: aircraft performance, battery technology, mission profile, mission economics, and electrical grid parameters. A sensitivity analysis is provided, comparing the operational performance and profitability of three electric VTOL concepts (lift plus cruise, quadcopter, and side by side), with respect to electrical grid and battery technology factors. The takeoff weight to maximize the number of completed routes or the overall profitability is also examined. Interestingly, results show that these two values do not coincide across the entire design space due to the nonlinearity of the battery life cycle with respect to the depth of discharge, which strongly affects battery replacement cost.

Markov Lifetime Prediction Model for Wireless Sensor Network

The Wireless Sensor Network (WSN) consists of sensor nodes that can communicate with each other via wireless transceivers to gather information from the environment. Sensor nodes are often placed in critical areas that are difficult to reach, sometimes in large numbers, and are unpredictable when the battery runs out on WSN. Thus, replacing the sensor node battery is difficult or even impossible. On the other hand, frequent battery replacement due to critical battery performance makes it uneconomical and unmeasurable. This paper proposes a lifetime battery prediction model for WSN. What is new in this study is that the battery lifetime is influenced by three factors, namely temperature, humidity, and data movement. Temperature and humidity significantly affect the battery lifetime, while data movement has little effect. Predictions of battery types one to four, with energy depletion (ED) consisting of Temperature, Humidity, and data movement. Each battery with these characteristics has a different lifetime; type one battery has a lifetime of 0.5 years, type two battery has a life of 0.16 years, type three has a life of 0.17 years, and type four has a lifetime of 0.4 years.

Design of Regenerative Braking System and Energy Storage with Supercapacitors as Energy Buffers

Vehicles are part of urban area transport and are subjected to variable loads as they traverse the city with varying slopes and stop-and-go traffic. Electric Vehicles (EVs) can be a good option because of their high efficiency under stop-and-go conditions and ability to gain energy from braking. However, limited battery energy makes EVs less efficient and degrades their lifetime. In contrast to a Li-Ion battery, supercapacitors work well under high power charge and discharge cycles. However, their high cost and low energy density prevent them from being viable replacements for batteries. Due to the slow charging and discharging process of batteries, they have a low power density, but a high energy density compared to the supercapacitor. In this paper, we discussed our system design consisting of both a battery and a supercapacitor. The main aim is to design and develop a scheduling algorithm to optimize energy flow between the battery, supercapacitor, and motor. We further described an analogue-based control methodology and algorithm for the supercapacitor, augmented battery-powered motoring process. This is in addition to a charge controller designed to optimize the supercapacitor bank's current-based charge-discharge profile. The system design and tests are developed on PSPICE and a hardware platform.

A solar-powered self-clean gas-sensing neural modulator for behavioral intervention with spatiotemporal flexibility

The amalgamation of high-sensitivity gas sensors with neural electrical stimulation technology stands as a compelling solution for eliciting behavioral responses in the presence of low-level hazardous gases. The utilization of battery-powered or coil-based configurations introduces spatiotemporal limitations, encompassing constrained experimental durations due to battery life or the necessity to confine subjects to specific locales for wireless power transmission. In this study, we present an advanced wireless neural modulator, meticulously engineered for behavioral intervention in unrestricted environments. This device integrates a solar-powered unit, gas sensor, brain stimulation signal management system, and a neurostimulation electrode. The solar energy utilization eliminates the necessity for battery replacements and local range limitations. The surface of the solar cells is treated with a superhydrophobic coating, enhancing performance in outdoor settings by mitigating surface contamination issues inherent in traditional solar cells. This innovation guarantees continuous, long-term, on-demand operational capacity, ensuring uninterrupted power supply to the system. Experimentation revealed shortened locomotor activity in mice, induced by stimulation of the periaqueductal gray (PAG) brain region, for up to thirty minutes. These results underscore the significant potential of our technology for spatially and temporally unrestricted neuromodulatory applications, offering a viable strategy to alleviate the detrimental effects of hazardous gas exposure on physiological functions.

Self-Powered Intelligent Water Droplet Monitoring Sensor Based on Solid-Liquid Triboelectric Nanogenerator.

Real-time monitoring of rainwater is a critical issue in the development of autonomous vehicles and smart homes, while the corresponding sensors play a pivotal role in ensuring their sensitivity. Here, we study a self-powered intelligent water droplet monitoring sensor based on a solid-liquid triboelectric nanogenerator (SL-TENG). The sensor comprises a SL-TENG, a signal acquisition module, a central processing unit (CPU), and a wireless transmission module, facilitating the real-time monitoring of water droplet signals. It is worth noting that the SL-TENG has self-powering characteristics and can convert the kinetic energy of water droplets into electrical energy. The excellent output performance, with open-circuit voltage of 9 V and short-circuit current of 2 μA without any treatment of the SL-TENG, can provide an effective solution to the problem that traditional sensor need battery replacement. In addition, the SL-TENG can generate stable amplitude electrical signals through water droplets, exemplified by the absence of decay in a short-circuit current within 7 days. More importantly, the sensor is equipped with intelligent analytical capabilities, allowing it to assess rainfall based on variables such as amplitude and frequency. Due to its excellent stability and intelligent analysis, this sensor can be used for roof rainwater monitoring, intravenous administration monitoring, and especially in automobile automatic wipers and other fields.

Progress and Prospect of Bimetallic Oxides for Sodium-Ion Batteries: Synthesis, Mechanism, and Optimization Strategy.

Sodium-ion batteries (SIBs) are considered as an alternative to and even replacement of lithium-ion batteries in the near future in order to address the energy crisis and scarcity of lithium resources due to the wide distribution and abundance of sodium resources on the earth. The exploration and development of high-performance anode materials are critical to the practical applications of advanced SIBs. Among various anode materials, bimetallic oxides (BMOs) have attracted special research attention because of their abundance, easy access, rich redox reactions, enhanced capacity and satisfactory cycling stability. Although many BMO anode materials have been reported as anode materials in SIBs, very limited studies summarized the progress and prospect of BMOs in practical applications of SIBs. In this review, recent progress and challenges of BMO anode materials for SIBs have been comprehensively summarized and discussed. First, the preparation methods and sodium storage mechanisms of BMOs are discussed. Then, the challenges, optimization strategies, and sodium storage performance of BMO anode materials have been reviewed and summarized. Finally, the prospects and future research directions of BMOs in SIBs have been proposed. This review aims to provide insight into the efficient design and optimization of BMO anode materials for high-performance SIBs.

Energy Efficient Quantum-Informed Ant Colony Optimization Algorithms for Industrial Internet of Things

One of the most prominent research areas in information technology is the Internet of things (IoT) as its applications are widely used such as structural monitoring, health care management systems, agriculture and battlefield management, and so on. Due to its self-organizing network and simple installation of the network, the researchers have been attracted to pursue research in the various fields of IoTs. However, a huge amount of work has been addressed on various problems confronted by IoT. The nodes densely deploy over critical environments and those are operated on tiny batteries. Moreover, the replacement of dead batteries in the nodes is almost impractical. Therefore, the problem of energy preservation and maximization of IoT networks has become the most prominent research area. However, numerous state-of-the-art algorithms have addressed this issue. Thus, it has become necessary to gather the information and send it to the base station in an optimized method to maximize the network. Therefore, we propose a novel quantum-informed ant colony optimization (ACO) routing algorithm with the efficient encoding scheme of cluster head selection and derivation of information heuristic factors. The algorithm has been tested by simulation for various network scenarios. The simulation results of the proposed algorithm show its efficacy over a few existing evolutionary algorithms using various performance metrics such as residual energy of the network, network lifetime, and the number of live IoT nodes.

Biodegradable triboelectric nanogenerator as a implantable power source for embedded medicine devices

Implantable medical devices have played an important role in human medicine in recent decades. However, traditional implanted devices require battery replacement and a second surgery for device removal, which can cause pain to the patient. This work presents a biodegradable triboelectric nanogenerator (BI-TENG) made from both natural and synthetic biodegradable materials that is utilized to collect mechanical energy in vivo and transduce it into electricity. Reed film and polylactic acid were chosen among different biodegradable materials as the triboelectric layers due to having the best generator output performance by providing voltages that reached 368 V. The biocompatibility of the friction layer and the device was verified via a blood test. After implantation in mice, the BI-TENG exhibited an open-circuit voltage of 0.176 V and a short-circuit current of 192 nA as generated from body movement. The BI-TENG was connected to an interdigital electrode to generate an electric field, which stimulated the accelerated release of doxorubicin (DOX) from red blood cells in targeted drug delivery systems. After stopping the electric field, the release of DOX normalized, facilitating the precise killing of cancer cells. Our work demonstrates the broad potential of BI-TENGs in the field of cancer treatment.

Powering the future: Exploring self-charging cardiac implantable electronic devices and the Qi revolution.

The incidence and prevalence of cardiovascular diseases (CVD) have risen over the last few decades worldwide, resulting in a cost burden to healthcare systems and increasingly complex procedures. Among many strategies for treating heart diseases, treating arrhythmias using cardiac implantable electronic devices (CIEDs) has been shown to improve quality of life and reduce the incidence of sudden cardiac death. The battery-powered CIEDs have the inherent challenge of regular battery replacements depending upon energy usage for their programmed tasks. Nanogenerator-based energy harvesters have been extensively studied, developed, and optimized continuously in recent years to overcome this challenge owing to their merits of self-powering abilities and good biocompatibility. Although these nanogenerators and others currently used in energy harvesters, such as biofuel cells (BFCs) exhibit an infinite spectrum of uses for this novel technology, their demerits should not be dismissed. Despite the emergence of Qi wireless power transfer (WPT) has revolutionized the technological world, its application in CIEDs has yet to be studied well. This review outlines the working principles and applications of currently employed energy harvesters to provide a preliminary exploration of CIEDs based on Qi WPT, which may be a promising technology for the next generation of functionalized CIEDs.

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.

Barriers to adoption of electric vehicles in Texas.

Sustainable mobility options such as electric vehicles (EVs) have the potential to improve the quality of life for Americans as well as those in other countries, as they can enhance the quality of the air we breathe, while reducing greenhouse gas emissions, fossil fuel consumption, and the adverse impacts of global warming. Despite their many benefits, however, the demand for EVs remains low. Therefore, this study aims to identify the barriers that affect the widespread EV adoption in the United States. Seventeen barriers were identified from the literature, and a questionnaire survey was designed and distributed to potential consumers of EVs. The survey yielded 733 responses, and various statistical tests like cluster analysis and chi-squared tests were performed. The results revealed that the high purchase price of the vehicle, high battery replacement cost, and the lack of public infrastructures for charging them were the primary concerns. The results also revealed that middle-aged men with high education and income are more enthusiastic about adopting EVs. The results presented in this study indicate a range of developments that different stakeholders could implement. To surmount the economic barriers to EV adoption, policymakers should strengthen incentives countrywide, and automakers should introduce more affordable EVs to the market. To overcome the challenges associated with charging, it is necessary to make investments in rapid charging infrastructure along the primary toll routes.

Analisis Keandalan Main Battery Peshawar CRJ-1000 Di Maskapai Garuda Indonesia

The main battery on the CRJ-1000 aircraft is an important component in the aircraft's electrical system. The main battery functions as the main source of electric power when the aircraft is turned off or when the aircraft engine is not operating. If there is a failure in the aircraft's battery it can cause disruption to other systems so that the aircraft cannot fly or Aircraft on Ground (AOG). In Garuda Indonesia's CRJ-1000 aircraft battery, there were several findings where the battery failed before reaching the scheduled removal time. This study aims to analyze the reliability of the CRJ-1000 main battery on the Garuda Indonesia airline. The analytical method is carried out by collecting historical data on main battery failures and calculating the Mean Time Between Failure (MTBF) and Availability values for a certain period. In addition, an analysis was also carried out on maintenance procedures and replacement of the main battery carried out by Garuda Indonesia airline technicians. The results of the analysis show that the MTBF of the CRJ-1000 main battery on Garuda Indonesia airlines has a fairly good value, but there is a need for improvement in maintenance procedures and replacement of the main battery to increase availability. The recommendations proposed are evaluating the main battery maintenance and replacement procedures, as well as increasing the availability of main battery spare parts which can speed up repair times in failure situations.

Design and Feasibility Study of A Stand-Alone Home Pv Solar System in Baghdad Climate

The question asked by all researchers is when solar panels will replace the national grid, especially in the domestic sector. In this study, a rooftop stand-alone solar electric system is designed to provide all the electrical power to a house in Baghdad-Iraq, using a (How to design PV system) simulation program. The feasibility of this system compared to the performance of the national electric grid and the system of private diesel generators is determined. The proposed solar system capacity is (25 kW), and the space required and the energy payback time are (360 m2 and 7.82 years), respectively. By using the current system, the net CO2 mitigation amount is 499,518.2 tons for 30-year. The kilowatt-hour costs for the subsidized national grid, private diesel generators, and the present solar system is 0.01865$, 0.1509$, and $0.108, respectively. The kilowatt cost can reach 0.25kWh if the battery replacement cost is estimated; so photovoltaic systems are still a good choice to generate electricity instead of using the national grid. If solar PV systems to generate electricity are used instead of the national grid, the financial and environmental profits will be good enough. The reason for the study is because the costs of off-grid solar PV systems are high, no specific studies have emerged on such vital topics. Currently, loans from government banks have reduced the impact of this negative factor

A Self-Localization Algorithm for Mobile Targets in Indoor Wireless Sensor Networks Using Wake-Up Media Access Control Protocol

Indoor localization of a mobile target represents a prominent application within wireless sensor network (WSN), showcasing significant values and scientific interest. Interference, obstacles, and energy consumption are critical challenges for indoor applications and battery replacements. A proposed tracking system deals with several factors such as latency, energy consumption, and accuracy presenting an innovative solution for the mobile localization application. In this paper, a novel algorithm introduces a self-localization algorithm for mobile targets using the wake-up media access control (MAC) protocol. The developed tracking application is based on the trilateration technique with received signal strength indication (RSSI) measurements. Simulations are implemented in the objective modular network testbed in C++ (OMNeT++) discrete event simulator using the C++ programming language, and the RSSI values introduced are based on real indoor measurements. In addition, a determination approach for finding the optimal parameters of RSSI is assigned to implement for the simulation parameters. Simulation results show a significant reduction in power consumption and exceptional accuracy, with an average error of 1.91 m in 90% of cases. This method allows the optimization of overall energy consumption, which consumes only 2.69% during the localization of 100 different positions.

Comparison of Discharge Performance of 12V/150Ah Gel and AGM Sealed Lead acid Batteries in Stand-alone PV-based Systems in UAE

This paper investigates the discharge performance of two major lead-acid batteries, namely 12V/150Ah Gel and AGM sealed lead-acid batteries, when operating in stand-alone (off grid) mode in photovoltaic (PV) based systems in United Arab Emirates (UAE). At harsh environmental conditions such as in UAE where the temperature can go to extremely high level in the summer, the battery performance and replacement cost increases the concerns about the reliability and economic feasibility of those batteries. This paper compares the discharge characteristics of those batteries through discharge tests performed on four similar batteries (two of each type). Experimental results of the discharge tests followed by a comparison between the two batteries are presented in this paper.

Research on human gait sensing based on triboelectric nanogenerator

To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly, a portable and low-cost triboelectric nanogenerator (TENG)-based self-powered sensor for human gait monitoring is proposed. The main fabrication materials of the TENG are polytetrafluoroethylene (PTFE) film, aluminum (Al) foil, and polyimide (PI) film, where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance. Exploiting the ability of TENGs to monitor changes in environmental conditions, a self-powered sensor based on the TENG is placed in an insole to collect gait information. Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals, the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status. Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%, demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.

Textured nanofibers inspired by nature for harvesting biomechanical energy and sensing biophysiological signals

Flexible electronics are emerging as a promising new platform for wearables; however, their practical utility is hindered by the limited battery life of electronic devices and the need for frequent battery replacements. Here, we report self-powered, flexible, permeable, tough, and lightweight biomechanical energy harvesting and biophysiological sensing devices using textured nanofibers for wearable electronics applications. The textured structure draws inspiration from two major sources of nature: the interior porous structure of jute fibers and the rough bark texture of trees. Interior pores are introduced to the nanofibers to increase compressibility and breathability like jute fibers. The inspiration from the rough bark texture also leads to a wrinkled surface morphology of the nanofibers to expand the surface area and consequently enhance toughness. To design and fabricate such a textured structure, the vapor-induced phase separation mechanism and electrospinning technique are employed within a controllable high humidity environment. Consequently, the textured nanofiber-based devices exhibit a well-rounded performance in electrical, mechanical, and physical properties, specifically demonstrating a significantly enhanced piezoelectric performance with more than two-fold electrical generation. These textured devices not only effectively harvest biomechanical energy from human movement but also demonstrate sensing capability for self-powered multifunctional biophysiological monitoring applications by leveraging the same piezoelectric mechanism. The novel design strategy for the textured nanofibers and their resultant balanced performance promotes the versatility and practical applicability of piezoelectric fibrous energy harvesting and sensing devices, contributing to the development of next-generation flexible and wearable electronics.

Forklifts, Automated Guided Vehicles and Horizontal Order Pickers in Industrial Environments. Energy Management of an Active Hybrid Power System based on Batteries, PEM Fuel Cells and Ultracapacitors.

The renewable energies together with other technologies in low CO2 emissions and the efficiency must be the base of the most sustainable new energetic system. Currently the logistics industry has a large number of vehicles (forklifts, horizontal order pickers, automated guided vehicles AGVs, tow vehicles, captive fleets applied to logistic...) intended to transport goods inside the plant. A problem associated with these logistic vehicles (electric or combustion type) is the charging time and balancing time in the batteries. Solution to the problem approached would be a system that requires a power charging times relatively short (similar to filling in the combustion system) and at the same time that have zero emissions (do not forget that they are operating in a closed environment). Typically, automated guided vehicles and forklifts are operated with lead acid batteries. The replacement of the traction battery with active hybrid power supply provide advantages as longer operating time, no recharging batteries, sizing of the fuel cell can be reduced and energy recovery during braking. Thus, energy management of an Active Hybrid Power System based on Li+ batteries, ultracapacitors and PEM fuel cells, is presented in this paper. Original lead-acid battery can be easily replaced by this new system implemented for industrial vehicles.