1. The Range Comfort Zone of Electric Vehicle Users Concept and Assessment Thomas Franke, Madlen Günther, Maria Trantow, Nadine Rauh, Josef F. Krems

2. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Usable range as challenge for BEV users Challenge: –improvement of BEV range = key challenge –Battery size = ecological footprint & cost effectiveness Objective: –provide users with maximum mobility resources (i.e., usable range) based on a given battery capacity –safeguarding an optimal user experience (i.e., avoid range anxiety) Possible solutions: –Driver information and assistance systems, training approaches, … Task for human factors research: –Evaluation of utility of range optimization strategies Research objective: –Examine comfortable range as a possible benchmark variable 1 Prolog | Concept | Assessment | Results | Conclusion lifetime mileage emissions

3. The Range Comfort Zone (1) Concept… 2 European conference on Human Centred Design for Intelligent Transport Systems 2014

4. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Understanding usable range Technical range vs. usable range: –Technical range (cycle range): objective range – assessment: driving cycle –Usable range: really comfortably accessible range – assessment: ??? Adaptive control of range (ACOR) framework – 3 psychological range levels: –Competent range – maximum achievable –Performant range – everyday available –Comfortable range – really usable (accessible) range Comfortable range = benchmark variable –Users’ preferred range safety buffer –Configuration of available resources & resource needs, still “best feeling state” Comfort zone concept – control theoretic models of driver behavior 3 Prolog | Concept | Assessment | Results | Conclusion

5. 4 European conference on Human Centred Design for Intelligent Transport Systems 2014 The Range Comfort Zone (2) …and Assessment

6. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Comfortable range scenario task (CRST) Scenario description: –… Imagine you are on a trip with your BEV on a familiar road in a rural area... 20°C … –… and you still have 60 km to drive before reaching your destination. –There are no charging possibilities en route. Yet, at the destination, … opportunity to recharge … Response grid: 5 Prolog | Concept | Assessment | Results | Conclusion 1. I am sure I will reach the destination with my EV. 77.5 Item scores: –i1: 77.5 km –i2: 72.5 km –i3: 72.5 km –i4: 82.5 km Mean score: –M = 76.25 km 2. I wish I had another car to make this trip. 72.5 3. I am concerned about reaching the destination. 72.5 4. On this trip, I will not be worried about range. 82.5

7. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Further comfortable range indicators Minimum range safety buffer (MinBuff): –“Which range buffer do you set for yourself, below which you would not be willing to drive the BEV anymore (except in exceptional circumstances)?” Proportional range safety buffer (PropBuff): –“In general, I want to have a safety buffer of x% in the battery. That is: What percentage should the displayed range be above the total trip distance?” Comfortable trip distance (ComfDist): –scenario description very similar to the CRST –“If the BEV shows a range of 100 km, I would still feel good about driving a total distance of up to x km” (ComfDist 100 ).  second item: “100 km”  “50 km”(ComfDist 50 ). 6 Prolog | Concept | Assessment | Results | Conclusion

8. 7 European conference on Human Centred Design for Intelligent Transport Systems 2014 The Range Comfort Zone (3) …and Results

9. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Data basis BMW ActiveE Leipzig – long-distance commuter field trial (2012-2015) N = 75 private users, 3 months BEV use Selection criteria: at least 90 km driving distance per day BEV: BMW ActiveE, around 130-160 km range For present talk: data from usage phases 1-2 (N = 29) MINI E Berlin 1.0 & 2.0 field trials (2008-2011) N = 110 private users, 6 months BEV use Urban mobility BEV: MINI E, around 160 km range 8 Prolog | Concept | Assessment | Results | Conclusion

10. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Results based on CRST Comfortable range vs. real range utilization behavior: –LDC: r = -.43, p =.027  CRST at T1  minimum displayed SOC of a user over entire trial 9 Prolog | Concept | Assessment | Results | Conclusion study time point NMM%M% αp T0T1 d T0T1 r T0T1 LDC (CRST) T02771.6 km84%.93.0050.58.70 T12767.2 km89%.97 ME1 (RG) T03784.6 km71%.91.0190.40.51 T13781.2 km74%.94 ME2 (RG) T01781.8 km73%.91.1270.39.43 T11779.1 km76%.93 Note. M % is proportional comfortable range utilization, α is Cronbach's Alpha, p-values are two-tailed, RG is range game (earlier version of CRST).

11. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Results based on further indicators Comfortable range vs. real range utilization behavior: –MinBuff r =.44, p =.017 –PropBuff r =.37, p =.046 –ComfDist 100 r = -.54, p =.003 –ComfDist 50 r = -.62, p <.001 10 Prolog | Concept | Assessment | Results | Conclusion item T0T0+1T1T2p T0T1 d T0T1 MinBuff M 13.8 km14.3 km7.4 km6.9 km <.0010.74 M% ‑‑‑‑ PropBuff M 12.4%15.0%11.1%9.9%.2270.23 M% 88%85%89%90% ComfDist100 M 85.0 km80.9 km92.1 km93.9 km.0020.63 M% 85%81%92%94% ComfDist50 M 39.1 km37.2 km43.2 km44.7 km.0890.33 M% 78%74%86%89% Note. M is in original item units, M% is proportional comfortable range utilization, p-values are two-tailed.

12. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Conclusion Methodology may provide a valuable tool for evaluating range-optimization strategies However: –Also some thing to keeps in mind when using this method –…and possible further improvements 11 Prolog | Concept | Assessment | Results | Conclusion

13. European Conference on Human Centred Design for Intelligent Transport Systems 2014 12 Thanks a lot for your attention! Contact: ActiveE@tu-chemnitz.de This study was funded by the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety. For further reading on comfortable range see for example: Franke, T., & Krems, J.F. (2013). Interacting with limited mobility resources: Psychological range levels in electric vehicle use. Transportation Research Part A: Policy and Practice, 48, 109-122. Franke, T., Neumann, I., Bühler, F., Cocron, P., & Krems, J.F. (2012). Experiencing range in an electric vehicle - understanding psychological barriers. Applied Psychology: An International Review, 61(3), 368-391. Franke, T., Cocron, P., Bühler, F., Neumann, I., & Krems, J.F. (2012). Adapting to the range of an electric vehicle – the relation of experience to subjectively available mobility resources. In Valero Mora, P., Pace, J.F., Mendoza, L. (Eds.). Proceedings of the European Conference on Human Centred Design for Intelligent Transport Systems, Valencia, Spain, June 14-15 2012 (p. 95-103). Lyon: Humanist Publications.

14. European Conference on Human Centred Design for Intelligent Transport Systems 2014 Conclusion Methodology may provide valuable tool for evaluating range-optimization strategies Things to keep in mind: –High degree of variability among individual scores (individual differences)  Interpretation in absolute sense: consider other statistical parameters (e.g., 80 th percentile of range safety buffers)  Design for all approach! –Comfortable range only one of three psychological range levels in ACOR model  CRST focuses on gap between comfortable & performant range  Yet: range elasticity also important design goal for range optimization –Gap between performant & competent range –Partly addressed in CRST, yet more direct assessment of perceived range elasticity advisable 13 Prolog | Concept | Assessment | Results | Conclusion