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
基本信息
- 批准号:551990-2020
- 负责人:
- 金额:$ 2.01万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Alliance Grants
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
In Canada and across the world, commercial vehicles are central to economic activity but are responsible for significant greenhouse gas emissions. Substantially reducing the climate impacts of goods transport without increasing costs is a major challenge. Combining existing engine technology with clean-burning fuels and a high-efficiency hybrid-electric powertrain offers a promising near-term approach to address this pressing problem. In this project, experts from the University of Alberta and Simon Fraser University will collaborate with Vancouver-based Westport Fuel Systems Inc. to investigate the potential emissions and fuel consumption benefits of a hybrid-electric commercial vehicle fueled with a range of low-carbon gaseous fuels.
The project will involve detailed modelling and optimization of the electric drive system, internal combustion engine, and on-board energy storage. The project will target a medium-heavy duty truck combined with a low-cost, high-efficiency natural gas engine as the main power source. The engine size and combustion system will be carefully optimized to match the required performance of the hybrid-electric powertrain. Simultaneously, the powertrain will be configured to make best use of the power provided from the engine while following the target drive profile. The additional benefits for both tailpipe and net greenhouse gas emissions from renewably generated gaseous fuels, such as bio-gas or hydrogen, will also be assessed. The results from this project will be the structural design of a commercially viable powertrain system that can provide dramatic reductions in greenhouse gas emissions for commercial transport.
在加拿大和世界各地,商用车是经济活动的核心,但也是温室气体排放的主要来源。在不增加成本的情况下大幅减少货物运输对气候的影响是一项重大挑战。将现有的发动机技术与清洁燃料和高效混合动力系统相结合,为解决这一紧迫问题提供了一种有前途的近期方法。在这个项目中,来自阿尔伯塔大学和西蒙弗雷泽大学的专家将与总部位于温哥华的韦斯特波特燃料系统公司合作。研究以一系列低碳气体燃料为燃料的混合动力电动商用车的潜在排放和燃料消耗效益。
该项目将涉及电力驱动系统、内燃机和车载储能的详细建模和优化。该项目的目标是一种中重型卡车,结合低成本,高效率的天然气发动机作为主要动力来源。发动机尺寸和燃烧系统将经过精心优化,以匹配混合动力系统所需的性能。同时,动力系将被配置成在遵循目标驱动曲线的同时最佳地利用从发动机提供的动力。还将评估可再生气体燃料(如生物气或氢气)的尾气排放和净温室气体排放的额外效益。该项目的成果将是一个商业上可行的动力系统的结构设计,可以为商业运输提供大幅减少温室气体排放。
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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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
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
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
Closed-Loop Predictive Control of a Multi-mode Engine Including Homogeneous Charge Compression Ignition, Partially Premixed Charge Compression Ignition, and Reactivity Controlled Compression Ignition Modes
多模式发动机的闭环预测控制,包括均质充气压缩点火、部分预混合充气压缩点火和反应性控制压缩点火模式
- DOI:
10.4271/04-16-01-0003 - 发表时间:
2023 - 期刊:
- 影响因子:1
- 作者:
Batool, Sadaf;Naber, Jeffrey;Shahbakhti, Mahdi - 通讯作者:
Shahbakhti, Mahdi
Shahbakhti, Mahdi的其他文献
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{{ 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:
$ 2.01万 - 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:
$ 2.01万 - 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:
$ 2.01万 - 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:
$ 2.01万 - 项目类别:
Discovery Grants Program - Individual
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
- 批准号:
RGPIN-2019-04601 - 财政年份:2019
- 资助金额:
$ 2.01万 - 项目类别:
Discovery Grants Program - Individual
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:
$ 2.01万 - 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:
$ 2.01万 - 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:
$ 2.01万 - 项目类别:
Postdoctoral Fellowships
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