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Research project within TUM CREATE. Focussing on modelling and optimisation of architecture and infrastructure, urban systems simulation like traffic and power are the main research interests. Apart from that, a cognitive systems group deal with human computer interaction. 

First glimpse of the effect of uncertainty on charging behaviour


First glimpse of the effect of uncertainty on charging behaviour

Vaisagh Viswanathan

How uncertainty influences the charging behaviour in a gamification approach

As an application to the previous article, we examine how uncertainty influences charging behaviour. Due to limited range and long charging time of electric vehicles (EVs),  the range anxiety phenomenon occurs in situation where the user might not reach the destination when low on battery (M. Nilsson 2011). While internal and personal factors are important factor regarding range anxiety (N. Rauh et al. 2014), we focus on external factors. Understanding charging behaviour will enable more optimal deployment of charging stations. In this article, the effect of uncertainty on charging behaviour is addressed using  a serious games approach or a game-based experiment.

The objective of the game, currently developed for iOS, is that the player delivers a certain number of  packages to locations around the map while taking as little time as possible. : the player knows all the locations beforehand, but in with order he chooses to collect and deliver the packages is up to the player (travelling salesman problem). In order to do this, the player uses an EV and needs to make decisions on which charging station to use and at what point of time. The player has a top-down view of the map and can choose packages, drop-off locations or charging stations as their destinations at any point of time. Information regarding a selected trip will also be shown to the player. 

In order to test the hypothesis that uncertainity has a role to play in charging behavior, we design four levels: one being the reference level and the other three being the experiment levels. All players play all the levels; however, the order of the experimental levels is completely counterbalanced. This is to ensure that the level order does not bias experiment results.  

There are three types of uncertainty introduced in this study. One uncertainty is the battery state of charge display being inaccurate: the displayed battery state of charge varies such that the player doesn’t know the exact amount that is left in the battery. Another uncertainty is that there is a probability that the charging station is out of operation when the player reaches there resulting in the need to choose an alternative. The last uncertainty is that range estimation circles replace the trip information. Instead of knowing the exact amount of energy required for that trip, only an estimate is provided to the player.

We have currently conducted a small pilot study with 10 participants to optimize the experiments and the game. The state of charge at each charging event is captured and analysed for each condition. Initial results indicate that the battery state of charge display and the charging station uncertainty have a signficant impact on the charging threshold for players when compared against the reference case. On the other hand,  the range estimation circle condition does not seem to show statistically significant difference to the reference condition. The reason for this is probably that the range estimation circles still provide enough information that allows the player to operate in a safe environment. We believe it would be interesting to  explore this situation further to find the underlying reason for this. If significant, this probably has an impact on how EV HUDs are designed in the future. (T. Franke et al. 2015) suggests that that the trustworthiness of the range estimation system in the EV can reduce the range anxiety. We eventually plan to use the charging behavior identified in this study as a basis for SEMSim simulation based analysis of charging station placement.