Exergy-Wise Predictive Control of Building and Automotive Energy Systems

建筑和汽车能源系统的火用预测控制

基本信息

  • 批准号:
    RGPIN-2019-04601
  • 负责人:
  • 金额:
    $ 1.97万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2019
  • 资助国家:
    加拿大
  • 起止时间:
    2019-01-01 至 2020-12-31
  • 项目状态:
    已结题

项目摘要

Building and automotive energy systems account for 57% of total energy use by consumers in Canada, while causing 36% of Greenhouse Gas (GHG) Emissions in Canada. The goal of this program is to develop new control methods to minimize energy consumption and GHG emissions from building and automotive energy systems. The short term objective of this program is to create a unified modeling and control theory for energy systems based on an ordered metric, “exergy,” i.e., the maximum theoretically available energy that can do work. This program will create a new paradigm for exergy-wise control through a novel theory based on the Second Law of Thermodynamics, Exergy Flow Controls, and Feedback Control Stability. The PI's recent results show exergy-wise control of Mechanical-Thermal-Chemical (MTC) energy systems provides opportunity for significant (7-36%) energy savings. Building upon the PI's results, the proposed research approach will include fundamental multi-physics exergy destruction modeling, exergy surface shaping, and thermodynamic flow control. The research program will center on MTC energy systems; applications of the theory will be demonstrated for internal combustion engines (ICEs) and building heating, ventilation, and air conditioning (HVAC) systems that cause over 46% of total energy use by consumers in Canada.***The long term goal is to extend the unified modeling and control theory framework from this program to include broad Mechanical-Thermal-Chemical & Electrical (MTCE) energy systems (e.g., hybrid electric vehicles) and connected MTCE energy systems (e.g., buildings-to-power grid systems). ******This program will train 11 Doctoral, Master of Science (MSc), and Bachelor of Science (BSc) students for developing unique skills to minimize energy consumption of MTC systems by using novel and powerful techniques of exergy-wise controls. The resulting knowledge from this program will be transferred to the relevant industry through planned industry short courses. In addition, new courses will be developed that will become available on-line for public use and outreach to the global research community.******Intellectual Merit: There is a significant knowledge gap between the controls research community and the thermodynamic research community that must be filled to enable exergy-wise control methods for energy systems. This research program aims to fill this knowledge gap.******Broader Impacts: The new exergy-wise control theory will be applicable to all mechanical-thermal-chemical systems. In particular, the application of the theory to ICEs in this program is anticipated to make a major contribution to the development of fuel-efficient ICEs that are widely used in automotive, power generation, oil & gas, marine, and rail industries. The second direct impact area includes energy saving for commercial & residential buildings HVAC systems that cause over 16% of the total energy use by consumers in Canada. **
建筑和汽车能源系统占加拿大消费者总能源使用的57%,同时在加拿大造成36%的温室气体(GHG)排放。该计划的目的是开发新的控制方法,以最大程度地减少建筑物和汽车能源系统的能源消耗和温室气体排放。该计划的短期目标是基于有序的指标“ Exergy”,即可以起作用的最大理论可用性能量,为能量系统创建统一的建模和控制理论。该程序将通过基于热力学,自我流量控制和反馈控制稳定性的第二定律来创建一个新的范式来进行锻炼控制。 PI的最新结果表明,机械热化学(MTC)能源系统的运动控制为大量(7-36%)节省的能源系统提供了机会。在PI的结果的基础上,拟议的研究方法将包括基本的多物理锻炼破坏建模,运动表面塑造和热力学流量控制。该研究计划将以MTC能源系统为中心;该理论的应用将用于内部燃烧发动机(ICE)以及建筑物的供暖,通风和空调(HVAC)系统,这些系统会导致加拿大消费者的总能源使用的46%以上。能源系统(例如,建筑物到功率网格系统)。 *****该计划将培训11个博士学位,科学硕士(MSC)和科学学士学位(BSC)学生,以开发独特的技能,以使用新颖而强大的锻炼控制技术来最大程度地减少MTC系统的能源消耗。该计划的最终知识将通过计划的行业短期课程转移到相关行业。此外,将开发新的课程,将在线使用,供全球研究社区提供公众使用和宣传。该研究计划旨在填补这一知识差距。****更广泛的影响:新的锻炼控制理论将适用于所有机械热化学系统。特别是,预计该理论在该计划中的ICES的应用将为开发燃油,发电,石油和天然气,海洋和铁路行业的开发做出重大贡献。第二个直接影响区域包括为商业和居民HVAC系统节省节能,这些系统会导致消费者在加拿大消费者总能源使用的16%以上。 **

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Shahbakhti, Mahdi其他文献

Data-Driven Model Learning and Control of RCCI Engines based on Heat Release Rate
基于热释放率的 RCCI 发动机数据驱动模型学习和控制
  • DOI:
    10.1016/j.ifacol.2022.11.249
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sitaraman, Radhika;Batool, Sadaf;Borhan, Hoseinali;Velni, Javad Mohammadpour;Naber, Jeffrey D.;Shahbakhti, Mahdi
  • 通讯作者:
    Shahbakhti, Mahdi
Input-output Data-driven Modeling and MIMO Predictive Control of an RCCI Engine Combustion
RCCI 发动机燃烧的输入输出数据驱动建模和 MIMO 预测控制
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Khoshbakht Irdmousa, Behrouz;Naber, Jeffrey Donald;Mohammadpour Velni, Javad;Borhan, Hoseinali;Shahbakhti, Mahdi
  • 通讯作者:
    Shahbakhti, Mahdi
Identification of State-space Linear Parameter-varying Models Using Artificial Neural Networks
使用人工神经网络识别状态空间线性参数变化模型
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bao, Yajie;Mohammadpour Velni, Javad;Basina, Aditya;Shahbakhti, Mahdi
  • 通讯作者:
    Shahbakhti, Mahdi
Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
  • DOI:
    10.1016/j.pecs.2021.100967
  • 发表时间:
    2021-10-23
  • 期刊:
  • 影响因子:
    29.5
  • 作者:
    Aliramezani, Masoud;Koch, Charles Robert;Shahbakhti, Mahdi
  • 通讯作者:
    Shahbakhti, Mahdi
Real-time modeling of ringing in HCCI engines using artificial neural networks
  • DOI:
    10.1016/j.energy.2017.02.137
  • 发表时间:
    2017-04-15
  • 期刊:
  • 影响因子:
    9
  • 作者:
    Bahri, Bahram;Shahbakhti, Mahdi;Aziz, Azhar Abdul
  • 通讯作者:
    Aziz, Azhar Abdul

Shahbakhti, Mahdi的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Shahbakhti, Mahdi', 18)}}的其他基金

Intelligent Control of Connected and Automated Vehicles and Powertrains for Cold Climates
适用于寒冷气候的互联自动化车辆和动力系统的智能控制
  • 批准号:
    RGPIN-2020-04403
  • 财政年份:
    2022
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Discovery Grants Program - Individual
Optimum high-efficient hybrid electric natural gas powertrain designs towards economically viable low emission trucks
优化高效混合电动天然气动力系统设计,打造经济可行的低排放卡车
  • 批准号:
    551990-2020
  • 财政年份:
    2021
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Alliance Grants
Intelligent Control of Connected and Automated Vehicles and Powertrains for Cold Climates
适用于寒冷气候的互联自动化车辆和动力系统的智能控制
  • 批准号:
    RGPIN-2020-04403
  • 财政年份:
    2021
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Discovery Grants Program - Individual
Intelligent Control of Connected and Automated Vehicles and Powertrains for Cold Climates
适用于寒冷气候的互联自动化车辆和动力系统的智能控制
  • 批准号:
    RGPIN-2020-04403
  • 财政年份:
    2020
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Discovery Grants Program - Individual
Optimum high-efficient hybrid electric natural gas powertrain designs towards economically viable low emission trucks
优化高效混合电动天然气动力系统设计,打造经济可行的低排放卡车
  • 批准号:
    551990-2020
  • 财政年份:
    2020
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Alliance Grants
Engine air fuel ratio control during cold phase to lower air pollution and reduce fuel consumption
冷态发动机空燃比控制,降低空气污染,降低油耗
  • 批准号:
    388139-2010
  • 财政年份:
    2012
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Postdoctoral Fellowships
Engine air fuel ratio control during cold phase to lower air pollution and reduce fuel consumption
冷态发动机空燃比控制,降低空气污染,降低油耗
  • 批准号:
    388139-2010
  • 财政年份:
    2011
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Postdoctoral Fellowships
Engine air fuel ratio control during cold phase to lower air pollution and reduce fuel consumption
冷态发动机空燃比控制,降低空气污染,降低油耗
  • 批准号:
    388139-2010
  • 财政年份:
    2010
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Postdoctoral Fellowships

相似国自然基金

基于piece-wise方法的横风横浪中破损船舶瘫船稳性及其倾覆机理研究
  • 批准号:
    51509124
  • 批准年份:
    2015
  • 资助金额:
    22.0 万元
  • 项目类别:
    青年科学基金项目
通过WISE巡天和MPA-JHU源表估算星系的恒星质量
  • 批准号:
    11563005
  • 批准年份:
    2015
  • 资助金额:
    47.0 万元
  • 项目类别:
    地区科学基金项目
用WISE红外卫星数据研究贫金属恒星形成星系性质
  • 批准号:
    11203001
  • 批准年份:
    2012
  • 资助金额:
    27.0 万元
  • 项目类别:
    青年科学基金项目
创造发明的方法研究及创造发明智能激励启发系统的研制
  • 批准号:
    59175189
  • 批准年份:
    1991
  • 资助金额:
    4.0 万元
  • 项目类别:
    面上项目

相似海外基金

Conference: Symposium on Early Career Women in Science and Engineering (WISE)
会议:科学与工程领域早期职业女性研讨会 (WISE)
  • 批准号:
    2411361
  • 财政年份:
    2024
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Standard Grant
パノラマX線画像から智歯と下顎管の三次元的位置関係を予測する説明可能な深層学習
可解释的深度学习从全景 X 射线图像预测智齿和下颌管之间的三维位置关系
  • 批准号:
    24K13108
  • 财政年份:
    2024
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Indigenizing Health Research Ethics in British Columbia with Indigenous Communities, Collectives and Organizations: Co-Create Wise Practices & Distinctions-Based Ethical Protocols in Indigenous Health Research
不列颠哥伦比亚省与土著社区、集体和组织的本土化健康研究伦理:共同创造明智的实践
  • 批准号:
    479951
  • 财政年份:
    2023
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Operating Grants
A Component-wise Model for Understanding Spin-Charge Interactions in Nanoparticle Solids Using Targeted Synthesis, Magnetometry, and Magnetoresistance
利用靶向合成、磁力测定和磁阻来理解纳米颗粒固体中自旋电荷相互作用的组件模型
  • 批准号:
    2322706
  • 财政年份:
    2023
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Continuing Grant
ATLAS: Assurance through layer-wise anomaly sensing
ATLAS:通过分层异常传感进行保证
  • 批准号:
    EP/X024288/1
  • 财政年份:
    2023
  • 资助金额:
    $ 1.97万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了