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Addressing Variation in Full Vehicle Automatic Transmission Fluid Fuel Economy Testing

机译:解决全车辆自动变速器流体燃料经济性检测的变化

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With government mandates, original equipment manufacturers are increasingly focusing on fuel economy and finding efficiency gains throughout the vehicle. Lubricant companies have been asked to design fluids that aid in this effort. Demonstrating real gains becomes complex given the intricacies of these systems and methods range from bench top screen tests to component test stands to full vehicle testing. This paper addresses the variation that was encountered when testing automatic transmission fluid efficiency within a full vehicle test. While it is well known that variability in testing conditions such as engine load or vehicle speed will lead to variability in results, the magnitude of their impact on average throughout the test cycle suggests that repeat testing may not be sufficient to guard against improper conclusions. In fact, our data indicates that typical differences in average conditions across the cycle can be associated with predictable impacts in test results of 0.7%-1% for vehicle fuel economy (in miles per gallon) when tested on the Highway Fuel Economy Test (HFET). In this paper we discuss an empirical model that quantifies the impact average operating conditions observed during the HFET test cycle can have on the miles per gallon reported for that cycle. This model explains differences between laboratories as well as replications over time at the same laboratory. In many cases normalizing test results to adjust for the average operating conditions could be an economical way to improve the ability to discriminate among fluids.
机译:通过政府任务,原始设备制造商越来越关注燃油经济性,并在整个车辆中找到效率。已经要求润滑剂公司设计有助于这项努力的液体。鉴于这些系统的复杂性和方法范围从台式测试到全车辆测试,鉴于这些系统和方法的复杂度,展示真正的收益变得复杂。本文解决了在全车辆测试中测试自动变速器流体效率时遇到的变化。虽然众所周知,在诸如发动机负荷或车速之类的测试条件下的可变性会导致结果的可变性,但在整个测试周期中平均影响的影响的大小表明,重复测试可能不足以防止不正确的结论。事实上,我们的数据表明,当在高速公路燃料经济性测试中测试时,循环跨越循环跨越平均条件的典型差异可能与用于车辆燃料经济性(每加仑数英里)的测试结果中的可预测的影响有关(HFET )。在本文中,我们讨论了一个经验模型,该模型量化了在HFET试验周期中观察到的影响平均操作条件可以对该循环报告的每加仑数英里。该模型解释了实验室之间的差异以及随着时间的推移在同一实验室之间的差异。在许多情况下,正常化测试结果调整平均操作条件可能是提高液体歧视能力的经济方法。

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