Smart powertrains for optimized fuel economy and reduced emissions

过去几十年见证了汽车系统和技术的巨大进步。然而，进一步增强以实现更好的性能仍然是非常可取的。拟议的研究包括预测控制策略的发展，该策略利用实时交通数据、GPS测量、3d路线图和现代车载探测器提供的信息来提高现有内燃机动力系统的效率。这些预测策略可以通过发动机和变速箱控制系统，以及现有的驾驶员辅助技术来实现，从而实现节能、安全、舒适的驾驶，同时降低排放，同时不会对行驶时间产生太大影响。这些发现对于提高带有额外组件的更复杂的动力系统架构的性能至关重要，例如微混合动力、轻度混合动力、全混合动力和插电式混合动力驱动系统，这些系统现在已经广泛应用。该研究项目为下一代智能混合动力系统的发展铺平了道路，该系统以最佳方式使用智能交通系统、全球定位系统、地理信息系统和先进的驾驶员辅助系统。汽车工业对加拿大经济非常重要。竞争压力和市场全球化给加拿大的汽车工业带来了新的挑战。预计该研究项目中开发的预测控制策略将在实践中节省约15%的燃油，减少约5-10%的污染物排放，而不会影响车辆的整体行驶时间。本地公司可以很容易地实施设计的控制算法，为向国外市场出口产品创造新的机会。培养高素质人才对加拿大经济也很重要。NSERC申请的资金将支持几名研究生开展拟议的研究目标。预计这些学生将在汽车和运输行业有就业机会。

The past decades have witnessed tremendous advances in automotive systems and technologies. However, further enhancements to achieve better performance are still highly desirable. The proposed research contains the development of predictive control strategies which utilize real-time traffic data, GPS measurements, 3-D road maps and information provided by modern vehicle on-board probes to enhance the efficiency of existing internal combustion engine powertrains. These predictive strategies can be implemented using engine and transmission control systems, and also, available driver assistance technologies, to achieve a fuel-efficient, safe and comfortable driving with lower emissions, without considerable effects on the travel time. The findings are critical to improve the performance of more complex powertrain architectures with extra components, such as micro-hybrid, mild-hybrid, full-hybrid and plug-in hybrid drive systems, which are now becoming widely available. This research program paves the way for the evolution of next-generation smart hybrid powertrains which use intelligent transportation systems, global positioning systems, geographic information systems and advanced driver assistance systems in an optimal manner. The automotive industry is very important for the Canadian economy. Competitive pressures and globalization of markets are introducing new challenges to Canada's automotive industry. It is expected that the predictive control strategies developed in this research program will cause approximate fuel savings up to 15% and pollutant emissions reductions of about 5-10% in practice, without affecting overall vehicle travel times. The local companies can easily implement the devised control algorithms to create new opportunities to export their products into the foreign markets. The training of highly qualified personnel is also important to the Canadian economy. The requested funding from NSERC will support several graduate students to carry out the proposed research goals. It is expected that these students will have employment opportunities within the automotive and transportation industries.