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Development and Optimization of a Novel, Ultrafast Aluminum-Ion Battery for Large-Scale Energy Storage Applications

Development and Optimization of a Novel, Ultrafast Aluminum-Ion Battery for Large-Scale Energy Storage Applications
用于大规模储能应用的新型超快铝离子电池的开发和优化
批准号:
515245-2017
负责人:
Sheikhzadeh, Mehdi
金额:
$5.46万
依托单位国家:
加拿大
项目类别:
Applied Research and Development Grants - Level 2
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31

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中文摘要
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英文摘要
Energy storage options that are reliable, long lasting and affordable are becoming an essential component in developing viable sustainable energy systems. Historically, lead acid batteries have been employed to store excess electrical energy, however, their short lifespan combined with their high maintenance requirements have limited their use. Lithium-ion batteries also have been extensively studied and installed for different applications; however, their high cost, environmental issues and shorter lifespan compared with aluminum-ion (Al-ion) batteries has further hindered their utilization in large-scale applications. Volta Energy Inc. and Lambton College in close collaboration through the proposed project will develop a novel, high-efficiency aluminum-ion battery capable of ultrafast charge and discharge with long cycle life exceeding those of state-of-the-art, commercially available secondary batteries, including lithium-based batteries. . In addition to single cell development and optimization, a series of battery banks, ranging from 1.0 kW to 25.0 kW, 30-minute (0.5 kWh to 12.5 kWh) will be developed and tested under varying operational conditions. Material development and optimization for different battery components, including anode, cathode and electrolyte with emphasis on the last two, will be the primary focused areas. The Lambton College research team will include IRCC Dr. Shahram Karimi, 2 graduate research students and 3 research students. The developed energy storage system into Volta Energy's industrial activities will greatly enhance their ability to serve their existing and future customers while creating economic growth and providing positive environmental impact for Canada.
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 财政年份:
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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  • 批准号:
    70601028
  • 项目类别:
    青年科学基金项目
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  • 批准年份:
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  • 负责人:
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  • 依托单位: