Ecodriving in hybrid electric vehicles--Exploring challenges for user-energy interaction

Energy Consumption Displays in Electric Vehicles: Differential Effects on Estimating Consumption and Experienced Energy Dynamics Awareness

OBJECTIVE

The effects of three prototypical designs of energy consumption displays on energy-specific situation awareness were examined.

BACKGROUND

Energy efficiency is crucial for the sustainability of technical systems. However, without accurate situation awareness of energy dynamics (energy dynamics awareness, EDA) it can be challenging for humans to optimize the use of energy resources of electric vehicles (EVs) through their behavior.

METHOD

We examined three prototypical energy display designs that varied by their informational value to support EDA. Furthermore, we investigated the differential effects on EDA measured by (1) a newly constructed scale (experienced EDA), (2) estimating energy consumption, and (3) identifying efficient trips in an online experiment. Participants (N = 82) watched standardized driving scenes (videos) of EV trips presenting the energy displays.

RESULTS

We found a strong effect of display type on experienced EDA, with the trace display being the most supportive. The EDA scale showed excellent internal consistency. The consumption estimation and efficient trip identification indicators were not affected by the display type.

CONCLUSION

The study indicates that experienced EDA is immediately affected by displays with higher information value, but performance might need more time and training. More research is needed to investigate the cognitive processes related to EDA and to examine how distinct display elements enhance EDA.

APPLICATION

Results from this research can be used as guidance for the design of energy displays, especially in EVs. The EDA scale can be used as an evaluation measure in the human-centered design process of energy displays.

Biased energy efficiency perception based on instantaneous consumption displays - Indication for heuristic energy information processing

Instantaneous consumption displays (ICDs) can be used as central information source to perceive the energy efficiency of manoeuvre-level driving. A key question is whether drivers who use ICDs can accurately derive energy efficiency differences of different driving strategies based on ICDs. There is reason to assume that drivers' consumption judgements may be biased, similar to driving-related phenomena like the time-saving bias. Therefore, the aim of the present research was to examine drivers' accuracy in deriving average consumption from dynamic ICD sequences. Participants viewed videos of a schematic ICD in a controlled experiment where the maximum instantaneous consumption systematically varied over time. Participants (N = 55) overestimated the average consumption values. The empirical ranking of the sequences did significantly correlate with the heuristic but not with the correct efficiency ranking. The current study incorporated multilevel modelling due to the nested structure of the data. The estimation difference was greater with higher peak height and shorter peak duration. The effect of peak height on estimation difference weakened with longer peak duration. In sum, the results indicate that ICDs can create biased perceptions of energy efficiency and that drivers seem to use simplifying heuristics. Knowledge and affinity for technology interaction appear to relate to biased estimations, whereas the intensity of prior experience with consumption displays seems irrelevant. Further studies should test other interfaces with debiasing potential such as manoeuvre-based aggregation or fading-trace approaches. Moreover, studies are needed that enable modelling of the effects of more natural temporal-spatial visual attention distribution (e.g. in a driving simulator setting).

Ideation using the "Design with Intent" toolkit: A case study applying a design toolkit to support creativity in developing vehicle interfaces for fuel-efficient driving

Everyday driving is a significant source of greenhouse gases and pollutants within developed nations. Finding ways to combat these emissions and minimise the impact of anthropometric climate change is a growing challenge for all research disciplines. This current paper explores the use of a design toolkit "Design with Intent" to generate ideas for in-vehicle interfaces designed to reduce fuel use and emissions. A preliminary interface validation assessment is also presented in order to assess whether the ideas generated were appropriate in encouraging behavioural change and of potential value. It is suggested that whilst further evaluation of the interfaces are required, the use of the "Design with Intent" toolkit facilitated the creative process, allowing engineers to conceive initial interface designs in a creative manner.

Introducing ergonomics requirements in the eco-design of energy-related products from users' behaviour approach

Ergonomics has been a very important activity in the design process. However, ergonomics rarely includes the environmental requirements into the design of products. The article proposes and presents the Eco-Ergo model through its application to a real-world product, a washing machine, to allow designers and ergonomists to establish product design requirements in order to minimise environmental impacts related to user-product interaction during the use stage. This model uses a visual language of representation, Blueprinting-based, that helps designers explore problems they have not previously considered during the market research when a wide variety of products with different interaction elements is analysed. The application of this model allows direct efforts and attention on the user analysis phase in the most influential user's actions on the environmental performance of energy-related products during use, establishing ergonomics requirements related to users behaviour at the initial design phase. Practitioner summary: This study provides a proposal to incorporate ergonomics into the practice of eco-design through the use of human factors in the establishment of initial eco-design requirements. This blueprint-based model combines an empirical and theoretical approach, based on the product test developed by designers, ergonomists and environmentalists. Abbreviations: CO2: carbon dioxide; DBIM: design behaviour intervention model; DfSB: design for sustainable behaviour; DwI Method: design with intent method; LCA: life cycle assessment; LCD: liquid cristal display; MJ: megajoule; MTM: methods-time measurement; PSS: product-service system; RPM: revolutions per minute.

Know-how or know-why? The role of hybrid electric vehicle drivers' acquisition of eco-driving knowledge for eco-driving success

Hybrid electric vehicles (HEVs) can contribute to sustainable transport. Yet, their real-world energy efficiency depends on HEV drivers' eco-driving behaviour. Eco-driving knowledge is key for successful eco-driving. The present research focused on the role of perceived strategy knowledge (know-how) versus technical system knowledge (know-why) in a study with 121 HEV drivers. The relationship between knowledge components and knowledge acquisition processes, as well as fuel efficiency, were examined. Structural equation modelling results indicated that perceived strategy knowledge was related to acquisition by testing (i.e., interacting with the vehicle and its interfaces) and reading (i.e., manuals, books and websites) while technical system knowledge was only related to acquisition by reading. In contrast to technical system knowledge, perceived strategy knowledge was no significant predictor of fuel efficiency. The results indicated that emphasis should be put into promoting technical system knowledge (e.g., by tutoring systems) to support motivated drivers' in achieving higher fuel efficiency.

What do people know about eco-driving?

An online survey of 321 respondents revealed that the majority of people are aware of eco-driving and have a positive attitude towards it. Although the types of eco-driving tips offered by respondents, and their potential effect on fuel consumption, were in line with those found in the popular and academic literature, knowledge of specific fuel saving behaviours was generally low. Relationships were found between environmental attitudes and knowledge of, and propensity to perform eco-driving behaviours; however, these relationships were weak, indicating that neither pro-environmental attitudes nor knowledge of eco-driving behaviours is strongly indicative of actual eco-driving performance. Males were found to be more knowledgeable of the means for driving in a fuel-efficient manner than females; however, no effect was found for either age or level of general education. Results are discussed in terms of the challenges and opportunities for encouraging eco-driving, and the necessity for both governmental and industry involvement. Practitioner Summary: To successfully encourage the uptake of eco-driving (e.g. through policy, training and feedback) it is first necessary to understand how the general public perceives it, and what they already know of it. This survey study addresses this by looking at relationships between environmental attitudes and knowledge, and specific eco-driving measures.

The Role of Interaction Patterns with Hybrid Electric Vehicle Eco-Features for Drivers' Eco-Driving Performance

OBJECTIVE

The objective of the present research was to understand drivers' interaction patterns with hybrid electric vehicles' (HEV) eco-features (electric propulsion, regenerative braking, neutral mode) and their relationship to fuel efficiency and driver characteristics (technical system knowledge, eco-driving motivation).

BACKGROUND

Eco-driving (driving behaviors performed to achieve higher fuel efficiency) has the potential to reduce CO₂ emissions caused by road vehicles. Eco-driving in HEVs is particularly challenging due to the systems' dynamic energy flows. As a result, drivers are likely to show diverse eco-driving behaviors, depending on factors like knowledge and motivation. The eco-features represent an interface for the control of the systems' energy flows.

METHOD

A sample of 121 HEV drivers who had constantly logged their fuel consumption prior to the study participated in an online questionnaire.

RESULTS

Drivers' interaction patterns with the eco-features were related to fuel efficiency. A common factor was identified in an exploratory factor analysis, characterizing the intensity of actively dealing with electric energy, which was also related to fuel efficiency. Driver characteristics were not related to this factor, yet they were significant predictors of fuel efficiency.

CONCLUSION

From the perspective of user-energy interaction, the relationship of the aggregated factor to fuel efficiency emphasizes the central role of drivers' perception of and interaction with energy conversions in determining HEV eco-driving success.

APPLICATION

To arrive at an in-depth understanding of drivers' eco-driving behaviors that can guide interface design, authors of future research should be concerned with the psychological processes that underlie drivers' interaction patterns with eco-features.