The energy consumption mechanisms of a power-split hybrid electric vehicle in real-world driving

With increasing costs of fossil fuels and intensified environmental awareness, low carbon vehicles, including hybrid electric vehicles (HEVs), are becoming more popular for car buyers due to their lower running costs. HEVs are sensitive to the driving conditions under which they are used however, and real-world driving can be very different to the legislative test cycles. On the road there are higher speeds, faster accelerations and more changes in speed, plus additional factors that are not taken into account in laboratory tests, all leading to poorer fuel economy. Future trends in the automotive industry are predicted to include a large focus on increased hybridisation of passenger cars in the coming years, so this is an important current research area. The aims of this project were to determine the energy consumption of a HEV in real-world driving, and investigate the differences in this compared to other standard drive cycles, and also compared to testing in laboratory conditions. A second generation Toyota Prius equipped with a GPS (Global Positioning System) data logging system collected driving data while in use by Loughborough University Security over a period of 9 months. The journey data was used for the development of a drive cycle, the Loughborough University Urban Drive Cycle 2 (LUUDC2), representing urban driving around the university campus and local town roads. It will also have a likeness to other similar driving routines. Vehicle testing was carried out on a chassis dynamometer on the real-world LUUDC2 and other existing drive cycles for comparison, including ECE-15, UDDS (Urban Dynamometer Driving Schedule) and Artemis Urban. Comparisons were made between real-world driving test results and chassis dynamometer real-world cycle test results. Comparison was also made with a pure electric vehicle (EV) that was tested in a similar way. To verify the test results and investigate the energy consumption inside the system, a Prius model in Autonomie vehicle simulation software was used. There were two main areas of results outcomes; the first of which was higher fuel consumption on the LUUDC2 compared to other cycles due to cycle effects, with the former having greater accelerations and a more transient speed profile. In a drive cycle acceleration effect study, for the cycle with 80% higher average acceleration than the other the difference in fuel consumption was about 32%, of which around half of this was discovered to be as a result of an increased average acceleration and deceleration rate. Compared to the standard ECE-15 urban drive cycle, fuel consumption was 20% higher on the LUUDC2. The second main area of outcomes is the factors that give greater energy consumption in real-world driving compared to in a laboratory and in simulations being determined and quantified. There was found to be a significant difference in fuel consumption for the HEV of over a third between on-road real-world driving and chassis dynamometer testing on the developed real-world cycle. Contributors to the difference were identified and explored further to quantify their impact. Firstly, validation of the drive cycle accuracy by statistical comparison to the original dataset using acceleration magnitude distributions highlighted that the cycle could be better matched. Chassis dynamometer testing of a new refined cycle showed that this had a significant impact, contributing approximately 16% of the difference to the real-world driving, bringing this gap down to 21%. This showed how important accurate cycle production from the data set is to give a representative and meaningful output. Road gradient was investigated as a possible contributor to the difference. The Prius was driven on repeated circuits of the campus to produce a simplified real-world driving cycle that could be directly linked with the corresponding gradients, which were obtained by surveying the land. This cycle was run on the chassis dynamometer and Autonomie was also used to simulate driving this cycle with and without its gradients. This study showed that gradient had a negligible contribution to fuel consumption of the HEV in the case of a circular route where returning to the start point. A main factor in the difference to real-world driving was found to be the use of climate control auxiliaries with associated ambient temperature. Investigation found this element is estimated to contribute over 15% to the difference in real-world fuel consumption, by running the heater in low temperatures and the air conditioning in high temperatures. This leaves a 6% remainder made up of a collection of other small real-world factors. Equivalent tests carried out in simulations to those carried out on the chassis dynamometer gave 20% lower fuel consumption. This is accounted for by degradation of the test vehicle at approximately 7%, and the other part by inaccuracy of the simulation model. Laboratory testing of the high voltage battery pack found it constituted around 2% of the vehicle degradation factor, plus an additional 5% due to imbalance of the battery cell voltages, on top of the 7% stated above. From this investigation it can be concluded that the driving cycle and environment have a substantial impact of the energy use of a HEV. Therefore they could be better designed by incorporating real-world driving into the development process, for example by basing control strategies on real-world drive cycles. Vehicles would also benefit from being developed for use in a particular application to improve their fuel consumption. Alternatively, factors for each of the contributing elements of real-world driving could be included in published fuel economy figures to give prospective users more representative values

Once upon a time, there was a fabulous funambulist: What children learn about the “high-level” vocabulary they encounter while listening to stories

Previous research has shown that listening to stories supports vocabulary growth in preschool and school-aged children and that lexical entries for even very difficult or rare words can be established if these are defined when they are first introduced. However, little is known about the nature of the lexical representations children form for the words they encounter while listening to stories, or whether these are sufficiently robust to support the child’s own use of such ‘high-level’ vocabulary. This study explored these questions by administering multiple assessments of children’s knowledge about a set of newly-acquired vocabulary. Four- and 6-year-old children were introduced to nine difficult new words (including nouns, verbs and adjectives) through three exposures to a story read by their class teacher. The story included a definition of each new word at its first encounter. Learning of the target vocabulary was assessed by means of two tests of semantic understanding – a forced choice picture-selection task and a definition production task – and a grammaticality judgment task, which asked children to choose between a syntactically-appropriate and syntactically-inappropriate usage of the word. Children in both age groups selected the correct pictorial representation and provided an appropriate definition for the target words in all three word classes significantly more often than they did for a matched set of non-exposed control words. However, only the older group was able to identify the syntactically-appropriate sentence frames in the grammaticality judgment task. Further analyses elucidate some of the components of the lexical representations children lay down when they hear difficult new vocabulary in stories and how different tests of word knowledge might overlap in their assessment of these components

Simulation study on the measured difference in fuel consumption between real-world driving and ECE-15 of a hybrid electric vehicle

Hybrid electric vehicles (HEVs) are sensitive to the driving conditions under which they are used, leading to greater fuel consumption than quoted by the manufacturer, and therefore higher CO emissions. Real-world driving can be very different from the legislative drive cycles as speeds are greater, there are faster changes in speed, and these changes occur at a greater frequency. This study aims to investigate where the differences between real-world driving and the ECE-15 urban drive cycle occur through development of a real-world drive cycle and via a system simulation study. A second generation 2004 Toyota Prius equipped with a GPS (Global Positioning System) data logging system was used to collect data while in use by Loughborough University Security over a period of 9 months. These data were used for the development of a drive cycle, Loughborough University Urban Drive Cycle (LUUDC), representing urban driving around the university campus and local urban area. The same vehicle was tested on a chassis dynamometer on the LUUDC against the ECE-15 cycle and others. Fuel consumption was measured and CO emissions were calculated and compared. A model based on Autonomie vehicle simulation software was used to simulate and analyse the differences. The test and modelling results showed higher fuel consumption on LUUDC than ECE-15. The reasons for this will be discussed in this paper

Simulation study on the measured difference in fuel consumption between real-world driving and ECE-15 of a hybrid electric vehicle

Hybrid electric vehicles (HEVs) are sensitive to the driving conditions under which they are used, leading to greater fuel consumption than quoted by the manufacturer, and therefore higher CO emissions. Real-world driving can be very different from the legislative drive cycles as speeds are greater, there are faster changes in speed, and these changes occur at a greater frequency. This study aims to investigate where the differences between real-world driving and the ECE-15 urban drive cycle occur through development of a real-world drive cycle and via a system simulation study. A second generation 2004 Toyota Prius equipped with a GPS (Global Positioning System) data logging system was used to collect data while in use by Loughborough University Security over a period of 9 months. These data were used for the development of a drive cycle, Loughborough University Urban Drive Cycle (LUUDC), representing urban driving around the university campus and local urban area. The same vehicle was tested on a chassis dynamometer on the LUUDC against the ECE-15 cycle and others. Fuel consumption was measured and CO emissions were calculated and compared. A model based on Autonomie vehicle simulation software was used to simulate and analyse the differences. The test and modelling results showed higher fuel consumption on LUUDC than ECE-15. The reasons for this will be discussed in this paper

Vertical flight training: An overview of training and flight simulator technology with emphasis on rotary-wing requirements

The principal purpose of this publication is to provide a broad overview of the technology that is relevant to the design of aviation training systems and of the techniques applicable to the development, use, and evaluation of those systems. The issues addressed in our 11 chapters are, for the most part, those that would be expected to surface in any informed discussion of the major characterizing elements of aviation training systems. Indeed, many of the same facets of vertical-flight training discussed were recognized and, to some extent, dealt with at the 1991 NASA/FAA Helicopter Simulator Workshop. These generic topics are essential to a sound understanding of training and training systems, and they quite properly form the basis of any attempt to systematize the development and evaluation of more effective, more efficient, more productive, and more economical approaches to aircrew training. Individual chapters address the following topics: an overview of the vertical flight industry: the source of training requirements; training and training schools: meeting current requirements; training systems design and development; transfer of training and cost-effectiveness; the military quest for flight training effectiveness; alternative training systems; training device manufacturing; simulator aero model implementation; simulation validation in the frequency domain; cockpit motion in helicopter simulation; and visual space perception in flight simulators

Author Correction: Rapidly-migrating and internally-generated knickpoints can control submarine channel evolution (Nature Communications, (2020), 11, 1, (3129), 10.1038/s41467-020-16861-x)

© 2020, The Author(s). The original version of this Article contained an error in the labelling of the cross-section in Fig. 2g and the vertical axis in Fig. 2b. This has been corrected in both the PDF and HTML versions of the Article