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Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles
Different processes can be used to provide inputs for regulation depending on the technology considered and the degree of validation of the models. Ideally, if all the models have been thoroughly validated, one would like to only perform simulations to provide regulatory inputs. Realistically, since the state-of-the-art models do not yet fulfill all engineering expectations (e.g., engine emissions or cold start), a combination of hardware and software will most certainly have to be used for the foreseeable future. A couple of examples highlighting the potential use of each process are given in Figure H-14.
To select a process to properly characterize a particular technology, it is compulsory to understand and quantify the uncertainties associated with each process. Examples of questions that need to be addressed within each process and in between processes are given below.
Uncertainty resides within each process and should be properly quantified. The following provides some examples for different processes.
Test facility to test facility variability. A 2002 report from the Automotive Testing Laboratory [source CRC E-55-1 Inter-laboratory Crosscheck of Heavy-Duty Vehicle D.PDF] highlights the discrepancies between several vehicle testing facilities. Figure H-15 shows significant differences among the six laboratories. The main difference (Lab C) is mainly due to high-altitude impact, while the smaller discrepancies among the other laboratories are related to a series of reasons ranging from testing process to road load curve to driver technique. However, it should be noted that for the truck employed, particulate matter (PM) was a species that is far more sensitive to test conditions than fuel use.
Test-to-test variability. While the testing conditions (e.g., temperature, humidity) are maintained constant during testing, several other factors affect dynamometer test results. One of the main factors is due to the driver, whether related to gear selection or engine on/off for hybrid vehicles. It is important to note that the driver model chosen in simulations will also affect results and is more repeatable than a human driver but must be chosen to be representative of a human driver.
While the impact can be important for conventional vehicles, especially when using manual transmissions, it is even more so for hybrid electric vehicles, due to