This innovative technology represents a forward-thinking approach to enhance the efficiency, safety, and overall performance of batteries, with a particular emphasis on Electric Vehicle
View moreOne or more embodiments of the present disclosure provide an intelligent temperature control and heat dissipation device for a new energy battery, which combines air cooling, liquid cooling,
View moreAuthors in [5] have described a novel method of hybrid PV/battery energy systems in a DC-coupled structure that can be adopted to solve the problem and replace fuel Cells. In [21] a hybrid PV/wave standalone hybrid PV/ wave energy conversion system with battery energy storage has been discussed. In this system, the bidirectional buck-boost DC
View moreNew energy power battery charging and discharging system platform. external circuit of the intelligent temperature control system is simple, which has the functions of good accuracy, high
View moreThe effectiveness of battery temperature control and the influence of the drive cycle on system performance have been examined: A fixed EEV control strategy, potential battery pack size mismatch, limited real-world drive cycle representation, and lack of comprehensive performance metrics: 9: Mohammadin & Zhang, 2015 [36] Prismatic LIB: 27: 1
View moreEnhancing the performance of electric vehicles (EVs) necessitates a strategic approach to managing the power battery system, with a pivotal focus on the Battery Thermal
View moreEffective thermal management of batteries is crucial for maintaining the performance, lifespan, and safety of lithium-ion batteries [7].The optimal operating temperature range for LIB typically lies between 15 °C and 40 °C [8]; temperatures outside this range can adversely affect battery performance.When this temperature range is exceeded, batteries may experience capacity
View moreThis thesis studies the development of the energy management system and control strategy of intelligent connected new energy vehicles and discusses the core techniques Among the influencing factors of the total capacity of the battery, the ambient temperature, the number of battery cycles, and the average discharge current are the key
View moreThe control of the integrated thermal management system of battery electrical vehicles mainly includes the thermal comfort control of the passenger compartment, the
View moreTechnical difficulties: New technologies need to be studied for cascade utilization, such as AI algorithm optimization of battery design and control scheme, intelligent charging and discharging technology, and lithium salt solution regeneration, pyrolysis and other technologies can also be used to improve the recycling efficiency of battery materials, which
View moreThe Battery Energy Management is a system which manages the electrical energy in a car by using a hardware control unit combined with three software modules: battery diagnosis, stop-mode
View moreIn addition, the experimental trial revealed that the surface temperature of the battery decreased by approximately 43 °C (from 55 °C to 12 °C) when a single cell with a copper holder was subjected to a TEC-based water-cooling system, with a heater provided with 40 V and the TEC module supplied with 12 V. Esfahanian et al. [87] implemented an air flow system
View moreThe invention relates to the technical field of battery temperature control, in particular to an intelligent control system for the temperature of a power battery of a new...
View moreFor instance, artificial neural networks (ANNs) have been utilized to model and control battery temperature in electric vehicles. Zhang et al. (2018) proposed an ANN-based temperature control system that utilized real-time data to predict battery temperature and
View moreThose strict regulations combined with ecological consequences of massive GHG emissions have prompted technical experts to explore energy-saving and emission-reduction technologies in ships, including novel hull and superstructure design, new propulsion systems, advanced energy management and operational optimization [12, 13] yond these
View moreThe control effect of the fuzzy-PID dual-layer coordinated controller is numerically evaluated, and the results show that it can maintain the average temperature of the Li-ion battery pack in the
View moreThe essential features of Intelligent Battery Systems are the accurate and robust determination of cell individual states and the ability to control the current of each cell by reconfiguration. They enable high-level
View more5) Based on machine learning models, the heat pump air conditioner monitors and adaptively adjusts ambient temperature and humidity, indoor temperature and humidity, air outlet temperature, battery temperature,
View moreBattery performance and safety can rapidly deteriorate when cell temperatures rise excessively high during operation and charging. This dangerous elevation in temperature is commonly referred to as
View moreTo meet the requirements of temperature self-adaptive control of battery thermal management system under different working conditions and to solve the problem that traditional temperature control strategy is challenging to achieve the two tasks of rapid cooling and temperature difference reduction in a single system, an intelligent temperature strategy for
View moreIn this work, a decentralized but synchronized real-world system for smart battery management was designed by using a general controller with cloud computing capability, four charge regulators, and a set of sensorized
View moreThis paper discusses the significance of temperature control of lithium battery in electric vehicle, and puts forward the optimization measures of operation mechanism of lithium battery...
View moreThe battery management system architecture is a sophisticated electronic system designed to monitor, manage, and protect batteries. She has been involved in leading and monitoring comprehensive projects when worked
View moreTherefore, the combination of deep learning technology and intelligent temperature control systems provides a new solution for precision manufacturing, not only promoting the digital transformation of the manufacturing industry in technology, but also demonstrating its strong potential and value in achieving energy-saving and emission reduction
View moreShe has been involved in leading and monitoring comprehensive projects when worked for a top new energy company before. She is certified in PMP, IPD,
View moreSelf-Adapting Intelligent Battery Thermal Management System via Artificial Neural Network Based Model Predictive Control August 2019 DOI: 10.1115/DETC2019-98205
View moreCurrently, lithium-ion batteries are dominant in the EV battery market due to their high power and energy density, high voltage, extended life cycles and low self-discharge rates (Nikolian et al., 2016).Nevertheless, lithium batteries are sensitive to aging and temperature; thus, special focus is required on their working environments to avoid any physical damage, aging,
View moreploy an MPC strategy along with three control modes, i.e. J-mode, U-mode, and Z-mode, to effectively control the battery temperature. The remainder of the paper is organized as follows. First, a lithium-ion battery electro-thermal model is devel-oped. Then, the optimization of grouped-channel J-type BTMS is conducted to uniform the battery
View moreThe smartification of heating systems is of significant importance for enhancing residents'' quality of life and reducing energy consumption. Addressing the inefficiencies, high energy consumption, and inflexible temperature control of traditional heating systems, this study aims to design an intelligent heating system based on IoT and STM32 microcontrollers.
View moreRelay output controlled the temperature closed loop control by single-chip microcomputer, and a new type of intelligent temperature control technology of electric blanket is developed, real-time
View moreThere is a deviation between the set value of the traditional control system and the actual value, which leads to the maximum overshoot of the system output tem
View moreDOI: 10.1016/j.applthermaleng.2023.121577 Corpus ID: 262052814; Intelligent temperature control framework of Lithium-ion battery for electric vehicles @article{Zhou2023IntelligentTC, title={Intelligent temperature control framework of Lithium-ion battery for electric vehicles}, author={Lin Zhou and Akhil Garg and Wei Li and Liang Gao},
View moreIn the new energy storage system, lithium-ion batteries (LIBs) have been widely used in new energy electric vehicles as the "power source" of electric vehicles due to their high energy density
View moreBYD releases the BYD DiSus Intelligent Body Control System, dedicated to new energy vehicles (NEV) with a lineup of DiSus-C, DiSus-A, and DiSus-P.
View moreBattery thermal management system is one of the most essential parts for the battery pack in electric vehicles. In this paper, a new battery thermal management system is developed through the
View more2 天之前· This paper presents a novel approach to battery thermal management control in Electric Vehicles (EVs), focusing on the establishment of a power loss model that incorporates
View moreOverall, the developed self- adapting intelligent J-type BTMS via ANN-based MPC is capable of controlling the temperature rise as well as the temperature uniformity in a reasonable range. This paper developed a self-adapting air-based J-type battery thermal management system.
This paper develops a self-adaptive control strategy for a newly-proposed J-type air-based battery thermal management system (BTMS) for electric vehicles (EVs).
Potential future work will in- tegrate the self-adapting J-type battery thermal system to- gether with the operations of other equipments like air con- ditioner for an optimal battery discharging scheduling.
The authors would like to thank Prof. Babak Fahimi and Dr. Zhuo Yang, at the Department of Electrical and Computer Engineering, The University of Texas at Dallas, for providing data on battery electro-thermal modeling. Pesaran, A., Santhanagopalan, S., and Kim, G., 2013.
Results showed that the optimized J- type BTMS has a 35.3% reduction in temperature rise, and a 63.4% improvement in temperature uniformity, with a cost of 7.5% augment in pressure drop compared to the bench- mark case. Based on the optimized J-type BTMS, an ANN-based MPC model was developed and tested with the UDDS driv- ing cycle.
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