Tool for qualitative performance comparison of internal combustion engines components using optimized engine calibration and condition monitoring
使用优化的发动机校准和状态监测对内燃机部件进行定性性能比较的工具
基本信息
- 批准号:522411-2017
- 负责人:
- 金额:$ 6.16万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 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
- 来源:
- 关键词:
项目摘要
Modern Internal Combustion Engines (ICEs) rely on complex control systems and engine maps in order to achieve higher fuel efficiencies while meeting stringent regulatory emissions standards. Given the economies of scale of the automotive sector, manufacturers strive to improve their engine technologies and even very small improvements in performance are considered. To adopt a new technology, techniques that can discern a measurable difference in the engine's performance are required to quantify the potential benefits of new components. NanoSpark, a Canadian start-up company, has developed an innovative spark ignition system for use in ICEs, believed to have a performance benefit. McMaster has in turn developed a method that can provide a qualitative and a quantitative comparison of components for ICEs. Our proposed technique uses conventional engine mapping in conjunction with multi-objective optimization in order to generate Pareto fronts that can be used for trade-off analysis. The comparison of Pareto fronts for existing and new components will enable us to quantify potential benefits or short-comings of new technologies across different operating ranges. This method will be used for quantifying the potential benefits of the NanoSpark spark plug and for analyzing its performance. The standard engine calibration tests will be used to provide a validation of the performance improvements indicated by the Pareto analysis. It is also necessary to verify the performance of the spark plug over time and to determine the impact of the new technology on other engine components. Traditionally this is evaluated by long duration testing under high engine stress. The McMaster research team has developed a number of signal-based condition monitoring strategies that could be used to reduce the amount of testing required for wear and impact analysis. Related to this analysis, it should be noted that many gasoline engines are now being equipped with direct injection fuel system, with a negative effect on the working life of the spark plug. As the NanoSpark technologies is expected to overcome this limitation, it is an ideal candidate for evaluating our signal-based condition monitoring methodology for this new application.
现代内燃机(ICES)依靠复杂的控制系统和发动机地图来实现更高的燃油效率,同时满足严格的法规排放标准。考虑到汽车行业的规模经济,制造商努力改进他们的发动机技术,即使是非常微小的性能改进也被考虑在内。为了采用一项新技术,需要能够识别发动机性能中可测量的差异的技术,以量化新组件的潜在好处。加拿大初创公司NanoSpark开发了一种创新的火花点火系统,用于冰块,据信具有性能优势。麦克马斯特反过来开发了一种方法,可以对冰的成分进行定性和定量比较。我们提出的技术将传统的引擎映射与多目标优化相结合,以生成可用于权衡分析的帕累托前锋。对现有部件和新部件的帕累托前沿进行比较,将使我们能够量化不同运营范围内新技术的潜在优势或不足。这种方法将被用来量化纳米火花塞的潜在好处并分析其性能。标准发动机校准测试将用于验证帕累托分析所表明的性能改进。还有必要验证火花塞随时间的性能,并确定新技术对其他发动机部件的影响。传统上,这是通过高发动机压力下的长时间测试来评估的。麦克马斯特研究团队开发了许多基于信号的状态监测策略,可用于减少磨损和冲击分析所需的测试量。与这一分析相关的是,应该注意的是,许多汽油机现在都配备了直喷式燃油系统,这对火花塞的使用寿命产生了负面影响。由于NanoSpark技术有望克服这一限制,因此它是评估我们针对这一新应用的基于信号的状态监测方法的理想候选者。
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)
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Habibi, Saeid其他文献
Kalman and Smooth Variable Structure Filters for Robust Estimation
- DOI:
10.1109/taes.2014.110768 - 发表时间:
2014-04-01 - 期刊:
- 影响因子:4.4
- 作者:
Gadsden, Stephen Andrew;Habibi, Saeid;Kirubarajan, Thia - 通讯作者:
Kirubarajan, Thia
Low Temperature, Current Dependent Battery State Estimation Using Interacting Multiple Model Strategy
- DOI:
10.1109/access.2021.3095938 - 发表时间:
2021-01-01 - 期刊:
- 影响因子:3.9
- 作者:
Messing, Marvin;Rahimifard, Sara;Habibi, Saeid - 通讯作者:
Habibi, Saeid
Parameter identification in a high performance hydrostatic actuation system using the Unscented Kalman Filter
- DOI:
10.1139/tcsme-2006-0024 - 发表时间:
2006-01-01 - 期刊:
- 影响因子:0.9
- 作者:
Chinniah, Yuvin;Habibi, Saeid;Sampson, Eric - 通讯作者:
Sampson, Eric
Estimating battery state of health using electrochemical impedance spectroscopy and the relaxation effect
- DOI:
10.1016/j.est.2021.103210 - 发表时间:
2021-09-10 - 期刊:
- 影响因子:9.4
- 作者:
Messing, Marvin;Shoa, Tina;Habibi, Saeid - 通讯作者:
Habibi, Saeid
Inner-Loop Control for Electro-Hydraulic Actuation Systems
- DOI:
10.1115/1.4001338 - 发表时间:
2012-01-01 - 期刊:
- 影响因子:1.7
- 作者:
El Sayed, Mohammed A.;Habibi, Saeid - 通讯作者:
Habibi, Saeid
Habibi, Saeid的其他文献
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{{ truncateString('Habibi, Saeid', 18)}}的其他基金
Advanced integrated Control and Monitoring of Actuation Systems
驱动系统的先进集成控制和监控
- 批准号:
RGPIN-2020-05735 - 财政年份:2022
- 资助金额:
$ 6.16万 - 项目类别:
Discovery Grants Program - Individual
Maximizing Information Extraction in Smart Condition Monitoring Systems
最大限度地提取智能状态监测系统中的信息
- 批准号:
CRC-2020-00127 - 财政年份:2022
- 资助金额:
$ 6.16万 - 项目类别:
Canada Research Chairs
Advanced integrated Control and Monitoring of Actuation Systems
驱动系统的先进集成控制和监控
- 批准号:
RGPIN-2020-05735 - 财政年份:2021
- 资助金额:
$ 6.16万 - 项目类别:
Discovery Grants Program - Individual
Maximizing Information Extraction In Smart Condition Monitoring Systems
最大限度地提取智能状态监测系统中的信息
- 批准号:
CRC-2020-00127 - 财政年份:2021
- 资助金额:
$ 6.16万 - 项目类别:
Canada Research Chairs
Condition monitoring and testing of powertrain elements
动力总成元件的状态监测和测试
- 批准号:
549016-2019 - 财政年份:2021
- 资助金额:
$ 6.16万 - 项目类别:
Alliance Grants
Hybrid Electric Vehicle Powertrain Design and Development
混合动力电动汽车动力总成设计与开发
- 批准号:
482038-2016 - 财政年份:2021
- 资助金额:
$ 6.16万 - 项目类别:
Collaborative Research and Training Experience
Tool for qualitative performance comparison of internal combustion engines components using optimized engine calibration and condition monitoring
使用优化的发动机校准和状态监测对内燃机部件进行定性性能比较的工具
- 批准号:
522411-2017 - 财政年份:2020
- 资助金额:
$ 6.16万 - 项目类别:
Collaborative Research and Development Grants
Condition monitoring and testing of powertrain elements
动力总成元件的状态监测和测试
- 批准号:
549016-2019 - 财政年份:2020
- 资助金额:
$ 6.16万 - 项目类别:
Alliance Grants
Advanced integrated Control and Monitoring of Actuation Systems
驱动系统的先进集成控制和监控
- 批准号:
RGPIN-2020-05735 - 财政年份:2020
- 资助金额:
$ 6.16万 - 项目类别:
Discovery Grants Program - Individual
Maximizing Information Extraction in Smart Condition Monitoring Systems
最大限度地提取智能状态监测系统中的信息
- 批准号:
1000233074-2019 - 财政年份:2020
- 资助金额:
$ 6.16万 - 项目类别:
Canada Research Chairs
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