Automating lubricating oil analysis as a means to reduce engine GHG emissions.

自动进行润滑油分析是减少发动机温室气体排放的一种手段。

• 批准号: 10006008
• 金额: $ 8.72万
• 依托单位: RAB MICROFLUIDICS RESEARCH AND DEVELOPMENT COMPANY LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10006008
• 关键词: Automating; lubricating; oil; analysis; means

Greenhouse gas (GHG) emissions from maritime transport is estimated at around 1 Bn ton of carbon dioxide equivalents (CO2 eq.) accounting for 3% of global anthropogenic emissions (IMO 2020). Emissions need to be cut by 50% up to 2050 to meet the Paris agreements (IMO 2020). Automation and digitisation have gained significant traction as enablers of greater efficiency in the maritime industry and can contribute meaningfully to reducing GHG emissions.RAB-Microfluidics have developed a microfluidic lab-on-a-chip technology that automates and digitises a key aspect of a shipping vessel operation -- Oil Condition Monitoring (OCM) which has the potential to enable marine engine efficiency, thereby reducing GHG emissions.OCM has remained relatively unchanged for over a hundred years with conventional wet chemistry techniques being the gold standard for industrial testing and analysis for engine condition monitoring. While these techniques deliver, robust compositional information, they are unable to provide to the desired frequency (because it is a manual process) data that can enable key insights to aid efficiencies and energy savings that lead to reduction in GHG emissions. RAB-Microfluidics lab-on-a-chip technology completely changes this as our technology automates the OCM process. Consequently, there is now the opportunity to plug that existing knowledge gap.In this project, we will integrate this technology with a live marine engine to continuously monitor the condition of engine condition during operation in real-time. Engine condition data will then be correlated with engine operation information (e.g., engine load, exhaust temperatures, shaft power/torque, engine speed, fuel pressure, etc.), performance data (e.g., energy efficiency plan, lube-oil consumption, fuel consumption etc.) and GHG emissions data to establish a cause-and-effect relationship. Such automation will allow generation of continuous streams of data on engine condition to provide insights that ensure the optimisation of marine engine operation/performance, permitting energy savings which will lead to reduction of GHG emissions. This potentially creates an offering that does not currently exist. This automation of the OCM process permits a potentially disruptive offering that transitions businesses from reactive to predictive operational strategies with the added potential to open up a £400Mn OCM automation market.This will be a first-of-its-kind development with potential to impact the reduction of GHG emissions. If successful, our technology will herald a stepwise change for the maritime sector helping maritime companies transition to next zero emission.

海运产生的温室气体排放量估计约为10亿吨二氧化碳当量。占全球人为排放量的3%（IMO 2020）。到2050年，排放量需要减少50%，以满足巴黎协定（IMO 2020）。自动化和数字化作为提高海事行业效率的推动因素获得了巨大的吸引力，并可以为减少温室气体排放做出有意义的贡献。RAB微流体开发了一种微流体芯片实验室技术，该技术可以自动化和数字化船舶操作的一个关键方面-油状态监测（OCM），该技术有可能提高船舶发动机的效率，OCM一百多年来一直保持相对不变，传统的湿化学技术是发动机状态监测的工业测试和分析的黄金标准。虽然这些技术提供了强大的成分信息，但它们无法提供所需的频率（因为这是一个手动过程）数据，这些数据可以实现关键的见解，以帮助提高效率和节能，从而减少温室气体排放。RAB-Microfluidics芯片实验室技术彻底改变了这一点，因为我们的技术使OCM过程自动化。因此，现在有机会填补现有的知识空白。在这个项目中，我们将把这项技术与一台实际的船用发动机结合起来，以实时连续监测发动机在运行过程中的状况。然后将发动机状况数据与发动机操作信息（例如，发动机负载、排气温度、轴功率/扭矩、发动机速度、燃料压力等），性能数据（例如，能源效率计划、润滑油消耗、燃料消耗等）和温室气体排放数据建立因果关系。这种自动化将允许生成关于发动机状况的连续数据流，以提供确保船舶发动机操作/性能优化的见解，从而实现节能，从而减少温室气体排放。这可能会创建当前不存在的产品。OCM过程的自动化允许潜在的颠覆性产品，将业务从反应性运营战略转变为预测性运营战略，并有可能开辟价值4亿英镑的OCM自动化市场。这将是首次开发，有可能影响温室气体排放的减少。如果成功，我们的技术将预示着海事部门的逐步变化，帮助海事公司过渡到下一个零排放。