Analysis and assessment of eco-driving strategies for train drivers training. Claudio Migliorini Stefano Ricci Eros Tombesi

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1 Claudio Migliorini Stefano Ricci Eros Tombesi

2 Topics Aims and working phases Factors affecting energy consumption Tools and available data Performance indicators Case study sections Presentation of main results Conclusions Possible future developments Page 2

3 Aims and working phases Phase 1 Aim Analysis and assessment of the present driving profiles. Activity 1 Assessment of the current behavior of driving staff and comparison with those of the real operation, in order to verify the reliability of the data from the simulator. Phase 2 Aim Analysis of driving profiles adopted in response to a generic instruction to adopt an "energy-efficient" drive. Activity 2 Analysis and assessment of the driving profiles adopted by the driving staff in response to the generic input of "energy-efficient driving" on the same routes taken into consideration during the first activity. Page 3

4 Energy Factors affecting energy consumption Train side Route side Train driver side Length and weight Full speed Longitudinal profile (total length, stations altitude, specifically start and end points) Speed profile (permanent speed limits and temporary speed limitations) Reduction of maximum speed Traction effort optimization, to achieve regime speed with less acceleration Full acceleration and deceleration Position, section and length of tunnels Coasting Traction effort and electric braking effort as a function of speed Curve radius Exploiting the infrastructure features of the line Motion resistances according to speed Additional resistances (e.g. for slopes and curves) Ability to recover braking energy and its actual use for trains simultaneously accelerating or accumulation Total traction and braking efficiency Number of stops Nominal characteristics of the electrification systems (current, voltage, frequency) Average voltage to the pantograph Space [km] = 17.22% Page 4

Tools The Dynamic Training Simulator (SIDAC) is located in the locomotives ex-depot Firenze Romito.

implements, among the others, technologies and concepts of condition based maintenance (CBM).

5 Tools The Dynamic Training Simulator (SIDAC) is located in the locomotives ex-depot Firenze Romito. It is able to reproduce the physical and sensory experience of the drivers while driving a Trenitalia regional transport E464 locomotive. Bombardier s remote diagnostics supports maintenance operations, realizing a technological platform that implements, among the others, technologies and concepts of condition based maintenance (CBM). From the remote diagnostics website is possible to download, among the others, RegEnergy.CSV files, showing various information referred to the whole E464 locomotives fleet of Trenitalia. Page 5

(Tensione) [V]: instantaneous value of the line voltage Current (Corrente) [A]: instantaneous value of the current absorbed by the train for its operation Space travelled (Km) [km] Pressure in the

6 Available data Dynamic Training Simulator (SIDAC) Time stamp (Timbro tempo) [hh:mm:ss]: time elapsed since the start of the simulation. It does not necessarily coincide with driving time Instantaneous speed (Velocità attuale) [km/h] Traction efforts (Trazione) [kn]: instantaneous traction (> ) and braking (< ) effort Voltage (Tensione) [V]: instantaneous value of the line voltage Current (Corrente) [A]: instantaneous value of the current absorbed by the train for its operation Space travelled (Km) [km] Pressure in the brake cylinders (Pressione CF1, Pressione CF2) [bar]: instantaneous pressure value in the brake cylinders; values indicate that the train is performing pneumatic service braking Energy (Energia) : cumulative net instantaneous energy value used during service. It is the result of the difference between the energy absorbed and the energy rendered during braking Bombardier s remote diagnostics Sample time [dd/mm/yyyy hh:mm:ss:nnn]: date and time of the service being examined at roughly one thousandth of a second SpeedAct-loco [km/h]: instantaneous train speed ZB-XFTB-MGr1 [kn]: instantaneous traction (> ) and braking (< ) effort MN-XU-Ln [V]: instantaneous value of the line voltage MN-XI-Ln [A]: instantaneous value of the current absorbed by the train for its operation Page 6

7 Performance indicators For evaluating each driving cycle, performance indicators have been developed to characterize it. Performance Indicator Symbol Definition Net energy En Energy needed to cover a specific section, net of the rendered quantity. Absorbed energy Ea Gross energy needed to cover a specific section. Rendered energy Er Energy recovered by using the electric brake during driving. Rendered energy [%] Er% Ratio % between energy rendered and net energy. Traction energy Et Energy needed for train movement. Stop energy Es Energy absorbed during the train stop phases. Specific consumption [kwh/km] Cs Relationship between net energy and length of the section. Travel time [min] T Travel time to cover a section. Advance / delay [min] A / R Difference between actual and planned travel time. Space travelled accelerating [%] Sa% Ratio % between acceleration space and total space. Space travelled cruising [%] Svc% Ratio % between cruising space and total space. Space travelled coasting [%] Sd% Ratio % between coasting space and total space. Space travelled breaking [%] Sf% Ratio % between braking space and total space. Page 7

21 (24.53 DD) Travel time [min] 25 Max speed [km/h] 15 Section M2: Montevarchi Pontassieve Stops [number] 6 Length [km] 33.

8 Main features: Case study sections 4 sections examined; 2 different service typologies: metropolitan (M) e regional service (RV). Section M1: Firenze SMN Pontassieve Section RV1: Firenze SMN San Giovanni Valdarno Stops [number] 5 Stops [number] 3 Length [km] 19.6 Length [km] (24.53 DD) Travel time [min] 25 Max speed [km/h] 15 Section M2: Montevarchi Pontassieve Stops [number] 6 Length [km] 33.6 Travel time [min] 3 Max speed [km/h] 16 Travel time [min] 31 Max speed [km/h] 16 Section RV2: Arezzo San Giovanni Valdarno Stops [number] 2 Length [km] Travel time [min] 27 Max speed [km/h] 16 Page 8

9 Activity 1 Assessment of the current behavior of driving staff and comparison with those of the real operation, in order to verify the reliability of the data from the simulator. Page 9

10 Section M1: Firenze Santa Maria Novella Pontassieve SIDAC Tele-diagnostic SIDAC Tele-diagnostic Travel Time [min] -1.74% Net Energy % Travel Time [min] 5 Specific Consumption [kwh/km] Traction Energy % Stop Energy % SIDAC Tele-diagnostic 6 5 Absorbed Energy -3.27% 4 3 Rendered Energy % 2 1 Specific Consumption [kwh/km] % -1 Net Energy Traction Energy Stop Energy Absorbed Energy Rendered Energy Page 1

11 Section RV1: Firenze Santa Maria Novella San Giovanni Valdarno SIDAC Tele-diagnostic SIDAC Tele-diagnostic Travel Time [min] 12.31% Net Energy 7.85% Travel Time [min] 14 Specific Consumption [kwh/km] Traction Energy 1.17% Stop Energy -52.5% SIDAC Tele-diagnostic Net Energy Traction Energy Stop Energy Absorbed Energy Rendered Energy Absorbed Energy 1.71% Rendered Energy 63.54% Specific Consumption [kwh/km] 7.4% Page 11

12 Corrente Assorbita [A] Tensione [V] - Corrente [A] Tensione [V] - Corrente [A] Conclusions about activity 1 In the case of the metropolitan service, in particular, the differences in the final result in terms of energy consumption are between 25 and 35%, while in terms of travel time to cover the route is up to 1%. Trenitalia's regional service drivers are not currently trained in terms of energetically efficient driving, which is why no attention has been paid to energy-related aspects; this obviously involves a difficult calculation of the amount of energy absorbed or rendered; Tensione Linea Spazio [km] Corrente Assorbita Auxiliary systems, during simulations, show energy consumption far above those found in the reports provided by the tele-diagnostic; Knowledge of the line brings advantages in terms of experience in real driving cycles, unlike simulated ones, conducted by driving staff from all over the country, who may have gone over the line for the first time Tensione Linea SIDAC Spazio [km] Corrente Assorbita Telediagnostica Tempo [min] Page 12

13 Activity 2 Analysis and assessment of the driving profiles adopted by the driving staff in response to the generic input of "energy-efficient driving" on the same routes taken into consideration during the first activity. Page 13

14 Section M1: Firenze Santa Maria Novella Pontassieve Travel Time [min] Net energy Traction energy Stop energy Absorbed energy Space travelled accelerating [%] -.84% Space travelled cruising [%] -8.11% Space travelled coasting [%] 3.77% Space travelled breaking [%].79% Specific Consumption [kwh/km] Rendered energy 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % Travel Time [min] -.45% Net Energy -1.72% Traction Energy -1.61% Stop Energy -3.66% Absorbed Energy -1.57% Rendered Energy 6.34% Specific Consumption [kwh/km] -1.73% 23.12% 23.3% 11.29% 14.77% 42.76% 39.29% 22.83% 22.64% Space Accelerating [%] Space Cruising [%] Space Coasting [%] Space Breaking [%] Page 14

15 Section M2: Montevarchi Pontassieve Travel Time [min] -.88% Net Energy -.15% Traction Energy -.49% Travel Time [min] Net Energy Traction Energy 19 Stop Energy Absorbed Energy Space travelled accelerating [%] 1.7% Space travelled cruising [%] -3.27% Space travelled coasting [%] -1.89% Space travelled breaking [%] 5.33% Specific Consumption [kwh/km] Rendered Energy 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % Stop Energy 6.94% Absorbed Energy.6% Rendered Energy 2.66% Specific Consumption [kwh/km] -.15% 23.18% 24.42% 2.4% 19.66% 34.24% 33.12% 22.54% 22.78% Space Accelerating [%] Space Cruising [%] Space Coasting [%] Space Breaking [%] Page 15

16 Section RV1: Firenze Santa Maria Novella San Giovanni Valdarno Travel Time [min] -1.18% Net Energy.38% Traction Energy.25% Travel Time [min] Net Energy Traction Energy 15.1 Stop Energy Absorbed Energy Space travelled accelerating [%] 2.31% Space travelled cruising [%] 3.47% Space travelled coasting [%] % Space travelled breaking [%] 1.11% Specific Consumption [kwh/km] Rendered Energy 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % Stop Energy 4.1% Absorbed Energy.65% Rendered Energy 5.77% Specific Consumption [kwh/km].38% 17.62% 17.82% 12.28% 9.86% 51.87% 53.67% 18.22% 18.64% Space Accelerating [%] Space Cruising [%] Space Coasting [%] Space Breaking [%] Page 16

17 Section RV2: Arezzo San Giovanni Valdarno Travel Time [min] -.24% Net Energy -1.1% Traction Energy -1.2% Travel Time [min] Net Energy Traction Energy 8.5 Stop Energy Absorbed Energy Space travelled accelerating [%] 1.94% Space travelled cruising [%] 1.58% Space travelled coasting [%] -4.78% Space travelled breaking [%].9% Specific Consumption [kwh/km] Rendered Energy 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % Stop Energy -5.32% Absorbed Energy -.85% Rendered Energy 2.99% Specific Consumption [kwh/km] -1.11% 33.43% 33.46% 17.81% 16.96% 35.2% 35.58% 13.73% 14.% Space Accelerating [%] Space Cruising [%] Space Coasting [%] Space Breaking [%] Page 17

18 Conclusions about activity(phase) 2 Data analysis available did not provide the expected results because: reduction in energy consumption is lower than 2% as a result of a generic "energyefficient" driving requirement; travel time of each section is reduced by less than 1%, while keeping most of the driving cycles completed late in time. To point out is the perceptible increase in the amount of energy produced in the transition between the two phases, ranging from 3% to 2%, demonstrating increased attention given by the train drivers to the braking technique in recovery. The results of this experiment indicate the need of training activities for train drivers aimed at a deeper insight into the issues related to energy saving. Knowledge of some energetically efficient driving techniques to acquire and maintain during simulator training can lead to a potential reduction in energy consumption, quantified in literature in the range 1 15%. Simple arrangements are, for example : reduction of cruising speed of along the longest sections, approximately longer than 1 kilometers; large use of coasting after reaching the maximum speed allowed in the sections, where the distance between two subsequent stops is within a few kilometers. Page 18

19 Possible future developments Proposal for introducing a supportive tool for conducting staff to facilitate the energetically efficient approach and subsequent learning audits; Collection all the simulated driving cycles during the two phases of the work, in order to identify the ones that have achieved the best result in terms of energy consumption; Subdivision of the 4 section considered in n sub-sections, each of which is delimited by two successive stations/stops in order to obtain a more comparable performance set; Determining the speeds of the most virtuous drivers from the point of view of energy saving, among all those who were able to meet the timetable provided by the train card, using the speed-space diagrams; Representation of the speed value identified for each section in the Train Speed" column of the train card, which now contains values identical to those in the "Maximum Speed" column, equal to the maximum speed allowed in that line section. Page 19

20 Velocità [km/h] Possible future developments Velocità Massima Distanze parziali Demo_Eco Spazio [km] Page 2

21 THANK YOU FOR YOUR KIND ATTENTION! Claudio Migliorini Stefano Ricci Eros Tombesi

Train Group Control for Energy-Saving DC-Electric Railway Operation

Train Group Control for Energy-Saving DC-Electric Railway Operation Shoichiro WATANABE and Takafumi KOSEKI Electrical Engineering and Information Systems The University of Tokyo Bunkyo-ku, Tokyo, Japan