## 5 Conclusions  
In the present paper, the results produced by a model for the estimation of the residual driving range of a L-7 BEV were reported. Several factors were included in the analyses, such as battery ageing, battery pack temperature, HVAC consumption and pre-heating through BTMS-related thermal management, to provide the reader with a comprehensive view of a larger set of parameters to be included when a realistic definition of the driving range of BEV is achieved. The data used for testing the model for the estimation of the residual driving range were extracted from an experimental campaign held within the H2020 STEVE project.  
First, the L-7 BEV backward-facing kinematic model was developed and validated on the experimental data. Then, the combined effect of battery ageing and battery pack temperature was assessed assuming a BTMS failure and four different amounts of battery ageing levels. The results proved the predominance of the ageing level on the overall performance of the battery and the convenience of shrinking the depth of discharge band in order to contain the loss of battery available capacity over time. After that, the effect of the HVAC power demand for heating and cooling the vehicle cabin on the BEV residual driving range was evaluated for winter and summer conditions, respectively. The results proved that an extended usage of the cabin conditioning system could be relevantly disadvantageous, even for a small BEV, regarding the reduction in vehicle performance. Finally, the convenience of pre-heating the battery through proper thermal management of the BTMS was assessed assuming the vehicle to be initially parked at 0\({}^{\circ}\) and \(-\)10 \({}^{\circ}\)C. Thanks to this analysis, the possibility of containing the reduction in the residual driving range by means of a pre-heating approach has been demonstrated. Furthermore, the amelioration given by employing the BTMS thermal management has been proved as much more efficient when the difference between the environment temperature and the optimal battery operating temperature increases.  
Our next research will focus on the development and validation of a battery ageing prediction model to replace the look-up table approach. In addition, an analysis of the benefits brought by a proper control policy of the HVAC on the performance of a BEV will be carried out. Finally, a smart thermal management policy of the BTMS will be studied to optimize the battery heating and cooling processes for different driving conditions.  
Conceptualization, G.C., C.M. and E.S.; methodology, C.M. and E.S.; software, G.C. and C.M.; validation, G.C.; formal analysis, G.C., C.M. and D.A.M.; investigation, G.C.; resources, G.C.; data curation, G.C. and C.M.; writing--original draft preparation, G.C., C.M. and D.A.M.; writing--review and editing, G.C., C.M. and D.A.M.; visualization, G.C., C.M. and D.A.M.; supervision, D.A.M. and E.S.; project administration, D.A.M. and E.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The work has been carried out in the frame of the Task 2.4 of the H2020-769944-STEVE project ([[http://www.steve-project.eu/index.php/en/](http://www.steve-project.eu/index.php/en/)]([http://www.steve-project.eu/index.php/en/](http://www.steve-project.eu/index.php/en/)), accessed on 8 September 2021), co-funded by the EC Horizon 2020 research and innovation programme. The partners of H2020 STEVE project are acknowledged for the support in the experimental testing campaign and the share of useful data.  
The authors declare no conflict of interest.