D8.1

Helsinki/Espoo: Demo Description and Implementation Plan

Version 1.0

Date of issue 30.11.2016

Nature of Deliverable External

Dissemination Level Public

Status Final

Issued by Project Director

Juhani Laurikko Michele Tozzi VTT UITP

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 636300. Coordinator: UITP – International Association of Public Transport

Deliverable 8.1 Page 1 of 32 SUMMARY SHEET Programme Horizon 2020 Contract N. 636300 Project Title European Bus Systems for the Future 2 Acronym EBSF_2 Coordinator UITP – International Association of Public Transport Project Director Michele Tozzi, [email protected] Web-site http://ebsf2.eu Starting date 1 May 2015 Number of months 36 months

Deliverable N. 8.1 Deliverable Title Helsinki: Demo Description and Implementation Plan Version 1.0 Date of issue 30 November 2016 Distribution [Internal/External] External Dissemination level Public Abstract The European Bus Systems for the Future 2 (EBSF_2) is an Horizon 2020 project to increase the attractiveness of public bus transport service and improve the econom- ic performance of the operators. The project consists of several city demonstrators including Helsinki demo. Technical innovations studied and demonstrated in Helsinki are an optimised and adaptive use of bus auxiliary devices and a driver assistance system. Objectives for these technical innovations are to decrease the energy consumption of the bus operations and to improve the accuracy and the riding comfort of the service. This document gives the description and implementation plan of the Helsinki demo. Background description of the technical innovations are given. Also key performance indicators chosen for the Helsinki demo to evaluate the results achieved by each implemented technical innovation in the demo tests are described. Keywords Auxiliary energy, driver assistance, back office system, real-time, self learning

This report is subject to a disclaimer and copyright. This report has been carried out under a contract awarded by the Euro- pean Commission, contract number: 636300 No part of this report may be used, reproduced and or/disclosed, in any form or by any means without the prior written permission of UITP and the EBSF_2 consortium. All rights reserved. Persons wishing to use the contents of this study (in whole or in part) for purposes other than their personal use are invited to submit a written request to the following address: UITP International Association of Public Transport Rue Sainte-Marie 6- 1080 Brussels

Deliverable 8.1 Page 2 of 32 INTERNAL DISTRIBUTION Participant N° Participant organisation name Country 1 Coordinator Union Internationale des Transports Publics - UITP Belgium 2 Régie Autonome des Transports Parisiens - RATP France 3 Iveco France SA - IVECO France 4 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. - FRAUNHOFER Germany 5 Hübner Gummi- und Kunststoff GMBH - HUEBNER Germany 6 DigiMobee SAS - DIGIMOBEE France 7 Centro de Estudios e Investigaciones Técnicas - CEIT Spain 8 Chalmers Tekniska Hoegskola AB - CHALMERS Sweden 9 Compañía del Tranvía de San Sebastián, SA (CTSS) – DBUS Spain 10 IRIZAR S Coop - IRIZAR Spain 11 D’Appolonia S.p.A. - DAPP Italy 12 EvoBus GmbH - EVOBUS Germany 13 Volvo Bus Corporation - VBC Sweden 14 Pluservice srl - PLUSERVICE Italy 15 Universidad Politécnica de Madrid - UPM Spain 16 Actia S.A. - ACTIA France 17 Teknologian Tutkimuskeskus - VTT Finland 18 MEL-SYSTEM Italy 19 Ineo Systrans – INEO France 20 Stuttgarter Strassenbahnen AG - SSB Germany 21 Associazione Trasporti - ASSTRA Italy 22 Pilotfish Networks AB - PILOTFISH Sweden 23 Start Romagna SpA - START ROMAGNA Italy 24 FIT Consulting Srl - FIT Italy 25 Hogia Public Transport Systems AB - HOGIA Sweden 26 Trapeze ITS UK Limited - TRAPEZE Switzerland 27 Digigroup Informatica srl - DIGIGROUP Italy 28 Transports de Barcelona SA - TMB Spain 29 TIS PT, Consultores em Transportes, Inovação e Sistemas, SA - TISPT Portugal 30 Rupprecht Consult - Forschung & Beratung GmbH - RUPPRECHT Germany 31 Keolis SA - KEOLIS France 32 Syndicat Mixte des Transports pourle Rhone et l agglomeration Lyonnaise - SYTRAL France 33 Transport for London – TFL UK 34 Università degli Studi di Roma La Sapienza – UNIROMA1 Italy 35 Verband Deutscher Verkehrsunternehmen - VDV Germany 36 Promotion of Operational Links with Integrated Services, Association Internationale - POLIS Belgium 37 Tekia Consultores Tecnologicos S.L - TEKIA Spain 38 Innovative Informatikanwendungen in Transport-, Verkehrs- und Leitsystemen GmbH - INIT Germany 39 Union des Transports Publics - UTP France 40 Västtrafik AB - VTAB Sweden 41 Commissariat à l’Energie Atomique et aux Energies Alternatives - CEA France 42 Consorcio Regional de Transportes de Madrid - CRTM Spain

Deliverable 8.1 Page 3 of 32 EXTERNAL DISTRIBUTION Entity Short name Country Contact person European Commission - INEA EC INEA - Mr. Walter Mauritsch

DOCUMENT CHANGE LOG Version Date Main area of changes Organisation Comments 0.1 14/09/2016 Draft of complete report VTT Creation of structure, draft and main content 0.2 7/10/2016 Update VTT 0.3 24/11/2016 Quality check UITP 1.0 30/11/2016 Modification based on VTT Final Version quality check

CONTRIBUTING PARTNERS Company Names Company Info VTT Juhani Laurikko Teknologian Tutkimuskeskus VTT Oy UITP Michele Tozzi International Association of Public Transport Rue Sainte-Marie 6, B-1080 Brussels, Belgium

ACRONYMS AVLS – Automatic Vehicle Location System AVMS – Automatic Vehicle Monitoring System CAN bus – Controller Area Network bus CCS – Combined Charging System DoW – Description of Work FEP – Front End Processor FMS – Fleet Management System HMI – Human Machine Interface HVAC – Heating, Ventilation, and Air Conditioning ICE – Internal Combustion Engine KPI – Key Performance Indicator OBU – On Board Unit PTa – Performance Target PTA - Public Transport Authority PTO – Public Transport Operator TI – Technological Innovation TS – Test scenario VO – Validation Objective WP – Working Package ZEV – Zero Emission Vehicle

Deliverable 8.1 Page 4 of 32 INDEX 1 Executive Summary...... 6

2 Introduction ...... 7

3 Background and context ...... 8 3.1 Geographical and urban context ...... 8 3.2 Local Public Transport System Overview...... 9

4 Objectives of the Demonstration...... 13

5 Demo description...... 15 5.1 General description of the Technological Innovations...... 15 5.1.1 TIHel1: ADAPTAUX...... 15 5.1.2 TIHel2: EDRIVEAID...... 15 5.2 Description of the demo line...... 15 5.3 Vehicles attending in the demonstration ...... 17 5.4 Optimal Driving Style for Electric City Buses (EDRIVEAID) ...... 19 5.5 Optimal operation of the auxiliary components (ADAPTAUX)...... 22

6 Demo implementation plan ...... 26 6.1 Demonstration structure...... 26 6.2 Demo team ...... 28

7 Partner Contribution...... 29

8 Conclusions ...... 30

9 References ...... 31 INDEX OF FIGURES Figure 1. The position of Helsinki metropolitan area and city of Espoo as part of it...... 8 Figure 2. An example of the appearance of busses in service of the HSL in the Helsinki metropolitan area (Photo: HSL)...... 10 Figure 3. An excerpt of the line and route map of the HSL for Espoo city centre area (Photo: HSL)...... 11 Figure 4. Positions of the current bus depots and their capacity in the HSL area (source HSL) ...... 12 Figure 5. Expected fleet composition strategy of Helsinki Regional Transportation (Figure: HSL) ...... 12 Figure 6. Line 11 on a map. A is Tapiola end and B is the Friisilä terminal ...... 16 Figure 7. An example of speed vs. time profile of line 11 driven from Friisilä to Tapiola ...... 16 Figure 8. “eMULE”, the prototype and test framework bus by VTT (Photo: VTT) ...... 17 Figure 9. Linkker Type 12R battery-electric bus (Photo: LinkkerBus)...... 18 Figure 10. Linkker Type 13 battery-electric bus (Photo: LinkkerBus) ...... 18 Figure 11. Linkker Type 12R battery-electric bus at a quick charging station situated in Tapiola (Photo: LinkkerBus)...... 19 Figure 12. In-service electric energy consumption of a test bus running on Line 11, in city of Espoo ...... 20 Figure 13. Communication between the components of the driver assistance system...... 21 Figure 14. On-board terminal device for driver guidance (Photo: VTT) ...... 22 Figure 15. Share of auxiliary component energy consumption in electric city bus during real-life operation ....23 Figure 16. Relation between bus speed and power consumption of the hydraulic pump ...... 24 Figure 17. Measured and modelled hydraulic pump power consumption...... 24 Figure 18. Simulated battery current, motor power and air compressor power for baseline and optimised air compressor operation...... 25

INDEX OF TABLES Table 1. Performance Targets and KPIs agreed for TIHel1 (ADAPTAUX) ...... 13 Table 2. Performance Targets and KPIs agreed for TIHel2 (EDRIVEAID) ...... 14 Table 3. Main dimensions of the Linkker busses Type 12R and Type 13 in Espoo demonstration...... 17 Table 4. Action list and timing for TIHEL1: ADAPTAUX...... 26 Table 5. Action list and timing for TIHEL2: EDRIVEAID...... 27 Table 6. Functions and roles of persons in the demo team with contact information...... 28

Deliverable 8.1 Page 5 of 32 1 Executive Summary

The overall objective of EBSF_2 is to increase the attractiveness and improve the image of the bus system in urban and suburban areas by demonstrating, evaluating and validat- ing in real operational scenarios the potential impact of technological innovations in de- veloping efficient solutions to both citizens and bus stakeholders’ needs. Six key research areas have been identified to have the highest potential to impact:  Energy Strategy and Auxiliaries;  Green Driver Assistance Systems;  IT Standards introduction in existing fleet;  Vehicle Design (capacity, accessibility, modularity);  Intelligent Garage and predictive maintenance; and  Interface between Bus and Urban infrastructure

These areas are to be further investigated in demonstrations in altogether 12 demo sites of which Helsinki is one. Technical innovations (TI) to be studied and demonstrated in Helsinki are an optimised and adaptive use of bus auxiliary devices and a driver assistance system. Objectives for these technical innovations are to decrease the energy consumption of the bus operations and to improve the accuracy and the riding comfort of the service.

This deliverable is intended to enlighten the Technical Innovations to be demonstrated in Helsinki , including the plans for implementation of the demonstrations as well as the se- lected quantitative and non-quantitative Performance Targets and the list of quantitative and qualitative Key Performance Indicators (KPI) that will evaluate the results achieved by each Technical Innovation implemented in the demo tests.

In addition, the information contained in this deliverable will establish the guidelines that will finally be used in the Global Evaluation procedure which will identify synergies among similar TIs, administer the economic and financial analysis of the TIs, and serve as a basis in order to assess the transferability guidelines for their implementation at other European sites.

Deliverable 8.1 Page 6 of 32 2 Introduction

The main objective of the demonstration in Helsinki Metropolitan area is to implement two new technological innovations (TI) on the operation of full-electric busses. These two TIs address two of the main Priority Topics of EBSF_2, namely:  Energy Strategy and Auxiliaries (TIHel1, “ADAPTAUX”)  Green Driver Assistance Systems (TIHel2, “EDRIVEAID”) The two innovations are based upon an innovation already implemented and successfully demonstrated in a fleet of ICE-powered busses, where the driver assistance system was able to lower overall fuel consumption by 5-10 % compared to the non-guided driving [1]. These fuel savings can make a noticeable improvement in the operating costs. In this demonstration the innovation will be further developed, and implemented (as TI- Hel2) in a bus with fully electric drivetrain in order to validate its potential. Furthermore, apart from assisting the driver to drive most economically, the other TI (TIHel1) will ad- dress the energy use of on-board auxiliaries in order to minimise their part in total losses of the vehicle and its operation. Because of the inherent high efficiency of the electric devices and systems (compared to ICE and mechanical drives) and lower price of electric energy (compared to transport fuels), cost savings due to lower use of energy are perhaps not the highest priority for energy savings. On the other hand, using less energy in operation means that either the range of the bus with a given battery capacity will become longer, extending the usability of the vehicle over the line network, or the battery capacity can be reduced with positive implications on mass and price. This element may prove to be more important than the direct running cost savings. More detailed descriptions of both TIs are given in Chapter 5, as well as the lists of Valida- tion Objectives (VO) chosen for demonstrating their functionality. The demonstration will take place in City of Espoo, which is the western part of the Hel- sinki Metropolitan area, which is the second-largest city in Finland with a population of 270 000 inhabitants. The total population of Helsinki Metropolitan Area is around 1.5 mil- lion, about one quarter of the total population of Finland (5.5 Million). In this part of the Metropolitan area the public transport system will undergo a fundamen- tal change, as the existing Metro railway now operating from Helsinki city centre towards east will soon be extended to the west, as well. This means that the direct bus lines now connecting south-western suburbs of Espoo to Helsinki city centre will be terminated, and replaced with shorter, feeder type of lines bringing passengers to their closest metro sta- tion only. This kind of change is very positive towards implementing fully electric busses, as the expected daily range in this type of operation is considerable shorter than in the previous lay-out.

Deliverable 8.1 Page 7 of 32 3 Background and context

3.1 Geographical and urban context The demonstration will be implemented in the City of Espoo, which is by population the second largest city in Finland, and forms the western part of the Metropolitan Helsinki area that holds about 25% of the total population of the country, being about 5.5 million inhabitants. The city of Espoo, along with the whole metropolitan Helsinki area, is situated in the southernmost part of Finland. Even so, it resides at the 60 latitude, and is some 1500 km north from most central parts of the Europe, and belongs to the Scandinavian climate, which is governed by the low pressure fronts moving over from the North Sea towards north-east. However, occasionally cold air from the Arctic can take over, and these cold spells are usually typified with almost no wind at all, and an inversion layer is formed over the populated area, hindering the disperse of the local pollution and keeping it close to the source with a negative impact on air quality. Figure 1 plots the positioning of both the Helsinki metropolitan area in Finland, and city of Espoo as part of it.

Figure 1. The position of Helsinki metropolitan area and city of Espoo as part of it

Due to the large geographical are of Finland (338 440 km2) and the relatively small population, the overall average population density of the country is very low (14 inh./km2). However, the population is not evenly spread, but is mostly focused on the south-western parts of the country, and especially around the city of Helsinki, the capital of the country.

Deliverable 8.1 Page 8 of 32 The city of Espoo covers some 300 km2 of land area, and has population density of about 900 inhabitants per km2. Thus it is less populated than Helsinki (some 3000 inh./km2), or even the other metropolitan area cities. Due to the global position and large geographical area of the country, Finland has a climate that is highly diversified. Although most of Finland lies on the taiga belt, the southernmost coastal regions where Helsinki area lies, are sometimes classified as hemiboreal, according to the Köppen climate classification1, and amongst all the Member States of the European Union, it may have the most diversified climate with daily maximum and minimum ambient temperatures ranging from -44 °C (all time low record) to +38 °C (all time high record)1. Even in the southernmost part of the country, where the Helsinki metropolitan area is located, the high-to-low swing over a 12-month period can be up to 60 °C. However, on coastal areas like Helsinki, temperatures below −30 °C are very rare. Winters in southern Finland (when mean daily temperature remains below 0 °C) are usually about 100 days long, and in the inland the snow typically covers the land from about late November to April, and on the coastal areas such as Helsinki, snow often covers the land from late December to late March1, but exceptions to this rule are abundant, especially during the past few decades. Climatic summers (when mean daily temperature remains above 10 °C) lasts in southern Finland from about late May to mid-September, and in the inland, the warmest days of July can reach over 35 °C1. On the positive side, the terrain in Finland is mostly very flat, and in the most-densely populated areas the elevation between the low and high areas remains less than 50 m. Even the highest point of public roads is about only 550 m above sea level. The demonstration is going to be set in an area where a well-established public transport service is available, but where also the competition between public transport and use of private passenger car is the fiercest in the area. Therefore, all positive attributes that can be affixed to the public/bus transport are of extremely high value. It is also important to note that the overall “big picture” of the public transport service is going to drastically change over the next few months due to the (overly late) commencing of the metro railway service towards the west, out from the existing city of Helsinki area that forms the centre and the east side of the Metropolitan area.

3.2 Local Public Transport System Overview The local public transport system in Helsinki Metropolitan area is governed by the local public transport authority (PTA) called Helsinki Regional Transport Authority (HSL)2. It is a municipal organisation, and its shareholders are the municipalities of the Metropolitan Helsinki. Current list includes Helsinki, Espoo, Vantaa, Kauniainen, Kerava, Kirkkonummi and Sipoo. HSL began its operations in 2010, but it is preceded with a similar type of organisation based on only four core cities of the region (Helsinki, Espoo, Vantaa, Kauniainen) that existed in 1970-2009.

1 https://en.wikipedia.org/wiki/Finland#Climate 2 https://www.hsl.fi/en/helsinki-regional-transport-authority

Deliverable 8.1 Page 9 of 32 HSL is in charge of planning and organising all public transport in the Metropolitan Helsinki area. The system consists of busses and trams, as well as local commuter trains and one metro railway line. As a curiosity, there is also one passenger ferry included. HSL does not own any vehicles, but organises the operations by tenders, awarded to a number of different Public Transport Operators (PTO). However, this does not apply to tram and metro services that are provided by the Helsinki City Transport (HKL), which is responsible for running the trams and the metro as well as construction and maintenance of track, stations and depots. HKL3 is a municipal enterprise and part of the City of Helsinki. It used to have also a division for bus operations, but it has been recently sold to a private bus company Koiviston Auto Oy, which is the largest privately-owned bus company in Finland consisting of seven different brands. It is active in both local and long- range bus transport services. Currently the local train operations are run by the state railway VR4, but there is an on- going effort to include also the trains into the tendered portion of the services, but current contract of VR extends to 2021. The number of PTOs involved in HSL services is about 10, and most of them belong to an international operator, like Transdev Finland, witch is a subsidiary of Transdev, a global public transport company, or Nobina, which is of Swedish origin, but has presence all over Scandinavia. In most cases the international presence has begun via acquisitions and mergers with local bus companies in this area. The total number of busses in daily use is around 1200. Even if the busses in the HSL area are operated by a host of different public transport operators, they all look very similar, as HSL mandates all busses to follow the same colour schemes and graphic design, and the operator’s logo is only seen at the back of the bus. Figure 2 depicts their current appearance.

Figure 2. An example of the appearance of busses in service of the HSL in the Helsinki metropolitan area (Photo: HSL)

3 http://www.hel.fi/www/hkl/en/ 4 http://www.vrgroup.fi/en/vrgroup/

Deliverable 8.1 Page 10 of 32 The busses in the HSL area are serving some 250 lines that are normally run between 5.30 and 23.30, with some special night lines, especially for the weekends. Figure 3 gives an excerpt of the line maps in the Espoo area, where the demonstration is to be implemented.

Figure 3. An excerpt of the line and route map of the HSL for Espoo city centre area (Photo: HSL)

The number of depots in the HSL area is around 20, serving between 20 to 300 vehicles per site. Figure 4 shows the positions of the current bus depots and their capacity as well as the name of the site.

Deliverable 8.1 Page 11 of 32 Figure 4. Positions of the current bus depots and their capacity in the HSL area (source HSL)

Because of the structure of the bus operations, it is not easy to make a break-down of the technology of the busses, but HSL has a strategy towards cleaner vehicles in their tender- based acquisition of public bus transport services with full-electric buses being the ultimate goal. At present, the break-down of their contracts consists predominantly of diesel buses, the EEV class being the majority with more than 60% share. However, by 2025 the goal for pure electric buses is 30 %, and together with hybrids, their combined share should reach half of the contracts. Figure 5 depicts this strategy as expeted fleet composition.

Figure 5. Expected fleet composition strategy of Helsinki Regional Transportation (Figure: HSL)

Deliverable 8.1 Page 12 of 32 4 Objectives of the Demonstration

The general main objectives of the demonstration are to (a) increase the attractiveness of public bus transport service by (b) improving the riding comfort of the service while (c) maintaining/improving the accuracy of the service (i.e. keeping up with the timetable). Furthermore, it shall (d) improve the economic performance of the operator by lowering the energy consumption of the bus operations. As a tool to achieve general main objectives, two TIs, Energy Strategy and Auxiliaries (TIHel1, ADAPTAUX), and Green Driver Assistance Systems (TIHel2, EDRIVEAID), are defined for the demonstration in Helsinki Metropolitan area on the operation of full-electric busses. The main validation objectives chosen for the two TIs are presented in Tables 1 and 2.

VO PT - Performance Targets KPI KPI definition/name Units

Average vehicle energy consumption Improve energy efficiency of 1 01.1 per km/Average fleet energy con- % fleets sumption per km Reduce the vehicle’s Average vehicle energy (fuel) con- 3 03.1 kWh/km energy consumption sumption per km Increase economic Total and amortization costs per €/(vehicle x 28 28.1 efficiency vehicle per 10,000 km 10,000 km)

Average energy demand by auxilia- Energy savings in auxiliary sys- 35 35.1 ries per km kWh/km tems

Table 1. Performance Targets and KPIs agreed for TIHel1 (ADAPTAUX)

Deliverable 8.1 Page 13 of 32 VO PT - Performance Targets KPI KPI definition/name Units

Average vehicle energy consumption Improve energy efficiency of 1 01.1 per km/Average fleet energy con- % fleets sumption per km Decrease harsh 06.1 Number of harsh decelerations (≤-2 events/ 2 6 decelerations 18.2 m/s ) per 100 km 100 km 18 Decrease harsh 06.2 Number of harsh accelerations (≥1.5 events/ 2 accelerations 18.3 m/s ) per 100 km 100 km Rate of more environmentally- % (im- conscious driving style by prove- Improve drivers' perception of drivers (non-guided/guided) ment) 7 more environmentally-conscious 07.1 driving styles Rate of more environmentally- Question- conscious driving style by naire/ drivers (acceptance) Score

CO emissions (simulated) kg/ 22 Mitigating air emissions 22.3 2 vehicle-km €/ Increase economic Total and amortization costs per (vehicle 28 28.1 efficiency vehicle per 10 000 km x10 000 km) Table 2. Performance Targets and KPIs agreed for TIHel2 (EDRIVEAID)

Deliverable 8.1 Page 14 of 32 5 Demo description

5.1 General description of the Technological Innovations The demonstration in the Helsinki Metropolitan Area will implement two technological innovations, labelled TIHEL1 and TIHEL2. TIHEL1, which is locally called “ADAPTAUX”, belongs to the EBSF_2 Topical Area of “Energy Stragegy and Auxiliaries. TIHEL2, which is locally called “EDRIVEAID”, belongs to the EBSF_2 Topical Area of “Driver Assistance Systems”. Both TI’s are basically based on a single data aquisition and back-office system that is supposed to improve both the driving style of the drivers as well as the strategy of running the auxiliaries of the electric-only driven bus.

5.1.1 TIHel1: ADAPTAUX TIHel1 is called “Adaptive Control for Auxiliaries in an Electric Bus”, and in short “ADAPTAUX”. It makes use of a real-time optimized control for auxiliaries on an electric bus. The TI is based on an innovative adaptation scheme that uses real-time data collection from the bus together with the real-time en-route position, traffic situation and characteristics of the line ahead to determine the optimum use of the auxiliaries. A back- office system collects all the data on-line, processes it, and feeds the bus with optimised use profiles in real time.

5.1.2 TIHel2: EDRIVEAID TIHel2 is called “Intelligent Driver Support System Applied to an Electric Bus”, and in short “EDRIVEAID”. Intelligent and adaptive driver assistance system implemented to help the driver to drive more energy efficiently while maintaining (or even increasing) passenger comfort and service quality (i.e. accuracy of the timetable). The system provides real-time guidance to drivers, taking into account vehicle en-route position compared to scheduled position, speed limit and the travelling comfort of passengers using recommendations on the intensity of acceleration and deceleration and feedback on current speed and its relation to the target speed.

5.2 Description of the demo line Both TIs are demonstrated in commercial battery-electric buses, operated by Transdev Finland Oy (a local subsidiary of Transdev SA), in real-world conditions and in real revenue service within an existing bus line (line 11) in the city of Espoo. The route is operated south and west to the local commercial centre Tapiola. Line 11 has 24 bus stops in 9.1 km or 26 bus stops in 10.1 km depending on the direction. The first bus starts at 5:42 and the last departure is at 23:47. Travel time one way is about 25 minutes, so the commercial speed is around 20-25 km/h depending on traffic. The profile of the line is mostly flat, with 85 % of the length being level, and less than 10 % both positive and negative slopes exeeding 2 %. The share of slopes more than ±6 % is less than 1 %. Figure 6 plots the line on a map. A is Tapiola end and B is the Friisilä terminal.

Deliverable 8.1 Page 15 of 32 Figure 6. Line 11 on a map. A is Tapiola end and B is the Friisilä terminal

Figure 7. An example of speed vs. time profile of line 11 driven from Friisilä to Tapiola

Deliverable 8.1 Page 16 of 32 5.3 Vehicles attending in the demonstration The first phase is to gather the “before” operation data of the buses for period of 6 months. The second phase is the actual demonstration of the assistant systems, and that will last 12 months. The data collection will be implemented first on a VTT’s “eMule” prototype bus, plus three commercial bussess, two Linkker Type 12R, and one Linkker Type 13. Table 3 lists some main characteristics of these busses.

Dimension Linkker Type 12R Linkker Type 13

Length [m] 12 m 13 m Height [m] 3.5 m (with pantograph) Width [m] 2.55 m Curb Weight [kg] 9 500 kg 10 100 kg

GVW [kg] 15 000 kg 16 000 Passenger Capacity 69 (40 seats) 76 (43 seats)

Motor Power [kW] 208 kW 208 kW

Battery chemistry Lithium Titanate Oxide (LTO)

Battery capacity [kWh] 55 kWh 55 kWh

Range [km] 30 to 50 km 30 to 50 km

Charging system CCS: Pantograph 200 kW and socket to 20 kW depot charger Table 3. Main dimensions of the Linkker busses Type 12R and Type 13 in Espoo demonstration

The “eMULE” prototype bus is depicted in Figure 8, and Figures 9 and 10 portray both Linkker bus types.

Figure 8. “eMULE”, the prototype and test framework bus by VTT (Photo: VTT)

Deliverable 8.1 Page 17 of 32 The Prototype bus will be used mainly for initial testing, but in the ADAPTAUX part of the demonstration the bus is in key role in assessing the impact of the Technical Innovation (TI). All of the Linkker buses will be used in generating the “before” and “during” data in both EDRIVEAID and ADAPTAUX demonstrations.

Figure 9. Linkker Type 12R battery-electric bus (Photo: LinkkerBus)

Figure 10. Linkker Type 13 battery-electric bus (Photo: LinkkerBus)

The battery capacity of Linkker busses is kept relatively small in view of low added weight and cost. Therefore, their operation relies on opportunity charging scheme. For the busses in Espoo demonstration one quick charge station has been erected in Tapiola end

Deliverable 8.1 Page 18 of 32 of the line. The busses have a pantograph connector (made by Schunk) and a fast charging system with 200 kW charging power for 3-7 minutes of recharging. The system is based on Combined Charging System (CCS) standard, which is a quick charging method supported by many automobile manufactures and controlled by the Charin consortium. This scheme is also tram system compatible with all the needed infrastructure support, and – if needed - enables 24h of continuous operation. Figure 11 shows Linkker Type 12R battery-electric bus on that charging station.

Figure 11. Linkker Type 12R battery-electric bus at a quick charging station situated in Tapiola (Photo: LinkkerBus)

5.4 Optimal Driving Style for Electric City Buses (EDRIVEAID) For studying the optimal driving style for electric city buses, measured data collected from real-world operation on actual bus line is used. The purpose of the study is to find out how the driving style affects electric bus energy consumption and to compare the identified optimal driving style with the optimal driving style of diesel buses. To identify the optimal driving style, the driving performances involving the lowest possible consumption are sought and their speed profiles are then analysed. The optimal driving style for electric busses is anticipated to differ from that of diesel buses. The main reason is the possibility for regenerative braking and differences in efficiency maps between an electric motor and a diesel engine. An example of variation in energy consumption is seen in Figure 12 where two drivers have been driving the same fully electric city bus on Line 11 in Espoo, Finland [2]. Runs are measured with the same bus and on the same line. This means that the variation in energy consumption shown in Figure 12 includes effects of different traffic and driving conditions, and runs are therefore not fully comparable. However, this large variation

Deliverable 8.1 Page 19 of 32 shows the potential for the driving style optimisation and also the need for comprehensive methods for bus operation assessment in changing traffic and driving conditions.

Figure 12. In-service electric energy consumption of a test bus running on Line 11, in city of Espoo

With the aid of driver assistance system, it is possible to affect the driver’s manner of driving in real-time. In a diesel city bus, economical driving is achieved by a quick acceleration and constant speed that is as low as possible. The system provides real-time guidance to drivers, taking into account vehicle position compared to scheduled position, speed limit and the travelling comfort of passengers using recommendations on the intensity of acceleration and deceleration and feedback on current speed and its relation to the target speed. When determining the guided speed the system dynamically takes into account the timetable: if the bus is ahead of schedule the constant speed can be lower. On diesel buses, saving potential of 5-10 % has been realized when the driver assistant system has been demonstrated and tested [1]. The better the driver follows guidance, the greater savings can be achieved. When the optimal driving style for an electric bus has been defined, the following procedure is identical to the diesel buses’ data collection, back office calculation and other required operations to achieve the driver assistance system to guide the bus driver for energy efficient driving, maintaining the speed limits and timetable (Figure 13). The collected data from buses and other sources during the operation is transferred wirelessly to a back office system consisting of a server software and browser-based user interface. The server software automatically processes and analyses data recorded on the bus line. The analysis reports can be viewed in the user interface. To operate, the guidance needs route-based instructions. For this, the necessary data, such as routes, timetables and speed limits, are collected from other systems by the server software. The route is presented to the terminal device as a list of GPS coordinate points with their target speeds, having information about the bus stops, speed limit

Deliverable 8.1 Page 20 of 32 changes and other possible factors. The route can be edited in the user interface, if some of the background data cannot be collected automatically.

Figure 13. Communication between the components of the driver assistance system

The on-board terminal device in the bus manages the measurement data collection and sending it to the server, and also the actual display of the guides for the driver. This on- board terminal device is shown in Figure 14. For the vehicle terminal, Aplicom vehicle computer is used. It has an internal GPS sensor and communication interface into to vehicle’s CAN bus. Usually at least two CAN buses exist in a bus, therefore two devices is also needed for one vehicle. The guiding code in the terminal is written in Java language. The vehicle terminal sends data into a server, which is implemented as a cloud service provided by the Microsoft Azure system. The server code, implemented in Java, runs in a virtual machine. After a learning period, the target speeds for the bus route will be calculated using the data that is collected during the operation. The location information as Global Positioning System (GPS) coordinates and vehicle speed with energy consumption are the essential variables for the monitoring system to compare with timetable. Using this background data, location-based target speed profiles will be created to each bus line and departure. Initial target speeds for the route can be, schedule permitting, e.g. 5% lower than the respective speed limits. The system will then adjust these speed instructions according to the learned optimal driving style.

Deliverable 8.1 Page 21 of 32 Figure 14. On-board terminal device for driver guidance (Photo: VTT)

The most recent addition for the driving assistant system is the functionality that enables the partial comparison of driving performances, allowing the analysis to focus on optimally driven stretches between bus stops or on even shorter stretches in order to construct optimum overall speed profiles. If these driving stretches and corresponding partial speed profiles are categorised to form general results, they can be used for adaption to other bus lines as well. Categories can be based on e.g. speed limits, stops and slow downs (traffic lights, speed bumps, pedestrian crossings and intersections) or length and shape (turns and hills) of the stretch.

5.5 Optimal operation of the auxiliary components (ADAPTAUX) In diesel buses, auxiliary device energy consumption consists of engine cooling fan, air compressor, air conditioning, power steering and alternator to run the 24 V devices such as lightning. For fully electric buses main auxiliary devices are electric powertrain cooling pump and fan, air compressor, power steering, HVAC system, and other devices such as lightning. In electric buses 24 V system feds all auxiliaries, and DC-DC converter is used for producing low voltage electricity from the high voltage of the traction battery. The energy consumption of auxiliary components in diesel-powered city buses was studied in different conditions [1]. During summer time, the average consumption for power steering has been reported to be under 1 % (in relation to energy available on crankshaft). In the same study, air compressor consumption was 2 % and air conditioning consumption 3 % of total energy consumption. During winter time, the auxiliary heater was responsible for 20 % of the total energy consumption. Albeit the relative energy consumption of the auxiliary components is low in diesel buses, the same amount of energy in an electric bus means higher relative portion from the total energy consumption. On the left in Figure 15, an example is shown about the energy usage of auxiliary components (from total battery energy) during operation in an actual bus line. In this

Deliverable 8.1 Page 22 of 32 example, consumption of Heating Ventilation and Air Conditioning (HVAC) is minimal, because the outside temperature was 15 °C and only small amount of heating or cooling with the air source heat pump is required. To produce maximum heating or cooling power, the energy consumed by this HVAC will be at least four times as much. During a cold winter day, additional heating would also be needed to maintain the cabin in a desired temperature. The extra power need can be four times the maximum power of the air source heat pump and a fuel-operated heater is required to produce the heat. Hence, with fully electric heating this would mean at least two times as much electric energy for heating as is used for the mandatory vehicle movement (rolling resistance, air drag, losses in electric powertrain, mechanical drive line, and mechanical brakes). In order to study and optimize the power consumption of the auxiliary subsystems, a simulation model of the vehicle and its auxiliary systems was developed. Main subsystems of the vehicle model are shown on the right in Figure 15. For the simulation model validation, an electric bus is driven on an actual bus route, Line 11 in Espoo, Finland, with bus stops and other traffic. The speed profile and the auxiliary component energy consumption are measured and utilised by the simulation model. [3]

Figure 15. Share of auxiliary component energy consumption in electric city bus during real-life operation

Stopping at bus stops and traffic lights and following the road with junctions and turnings require steering, braking and opening the bus doors. Auxiliary device consumption is thus dependent on the bus route and also on the ambient conditions which demand using HVAC for passenger and driver comfort. Power consumption of the auxiliary devices is modelled using a system identification approach. The electricity consumption of the power steering and air compressor has been measured. Based on the measurement data and the bus route, simple mathematical models of the energy consumption of the given auxiliary devices can be created. Energy consumption of the power steering is related to the operation of the hydraulic pump. Based on the measurement data, power consumption of the hydraulic pump correlates with the bus speed. When the bus is stopped in traffic lights or on a bus stop, for example, the power consumption is zero. Otherwise, the consumption is relatively constant. The measured bus speed and power consumption of the hydraulic pump are shown in Figure 16. Based on this relation, a model of the power consumption was

Deliverable 8.1 Page 23 of 32 created. The measured and modelled power consumptions are shown in Figure 17. The cumulative power consumption in both cases was about 0.49 kWh. The model was also validated with another dataset from the same bus line, resulting in cumulative power consumption of 0.37 kWh while the measured consumption was 0.36 kWh. This indicates that the simulation model gives reliable and accurate results.

Figure 16. Relation between bus speed and power consumption of the hydraulic pump

Figure 17. Measured and modelled hydraulic pump power consumption

Power consumption of the hydraulic pump can be optimised by switching the pump off when power steering is not used. In a case where the power consumption of the pump is set to zero when the turning angle of the bus is zero was simulated. This optimised power consumption is 0.35 kWh which is 27 % less than without the optimisation scheme. With the validation dataset, the optimised consumption is 0.29 kWh which means 20 % power saving. This was 1.6 % of total energy consumption. The potential of utilizing an optimal air compressor operation to reduce overall energy consumption was also examined. The potential for energy savings comes from the use of regenerated power directly in the air compressor during regenerative braking. If the energy is stored to the battery, battery losses are present resulting from the average battery efficiency, which is usually around 96 %. Another aspect is the limited charging current of the battery, which will limit the regenerative motor power. The charging current of the battery is extremely sensitive for the battery temperature, and during the winter time, the permitted current can decrease into at least one third of the maximum. However, the regenerative power could be increased if there was alternative electric load available. For this purpose, the compressor was modified to activate only at adequately long and hard decelerations, when it is normally activated based on air consumption, and this approach increases the regenerative power and regenerated energy relative to the limits defined by the battery.

Deliverable 8.1 Page 24 of 32 In Figure 18, results of using the modified and normal compressor activation strategy are compared. The air compressor energy consumption was equal in both strategies. The battery charging limit was set to 45 A, which represents the actual measured limit permitted by the Battery Management System (BMS) in +3 °C ambient condition. In Figure 18 a partial stretch of the cycle is presented and the differences for battery and motor operation can be seen when the baseline or modified air compressor activation strategy is used. Energy saving is achieved because of the higher regenerative motor power and avoiding the unnecessary charging and recharging losses of the battery.

Figure 18. Simulated battery current, motor power and air compressor power for baseline and optimised air compressor operation

The realized cumulative savings during the whole cycle was 0.13 kWh, which means 1.6 % decrease for the overall vehicle energy consumption. The total consumption of the compressor was 0.56 kWh during the cycle. All of this potential is not available for recovery, because the system is already in baseline operation inherently feeding the energy for consumers during the regenerative braking. In addition, the timing of the compressor usage in the baseline is often occurred during the hardest decelerations, and on the other hand, many of the additional compressor activation in the modified strategy occur in low power regeneration and current limit is not met. Although the achieved energy saving was small on this particular case, higher savings can be anticipated when also the HVAC usage will be optimized. This could include boosting HVAC power when braking, thus storing braking energy as cold/hot air in the cabin making it possible to switch off HVAC for some time. The speed profile of the Line 11 had only modest decelerations, and therefore the battery current limit was exceeded only few times. On more dynamic cycle the saving potential could be higher.

Deliverable 8.1 Page 25 of 32 6 Demo implementation plan

6.1 Demonstration structure In the EDRIVEAID part of the demonstration, the generation of “before” data begins in late 2016, ending during the spring 2017. Already during this phase one back office system will start to work on generating the optimal speed profiles. During phase two the profiles will be taken into action but the system will continue data collection and improving the profiles. The phase two starts during spring 2017 and lasts one year. The optimal energy strategy guidance (ADAPTAUX) will follow the same strategy but with later schedule. This is because ADAPTAUX part has some preceding tasks. First, the strategy shall be planned using a simulation model and after that verified with measurements on a chassis dynamometer. In the autumn 2017, the strategies are tested en-route operation and also demonstrated in small scale. The reference data for ADAPTAUX is collected during phase two of EDRIVEAID and also demonstrated later to separate the EDRIVEAID effect of the ADAPTAUX effect. For both EDRIVEAID and ADAPTAUX the testing will be done using shorter periods with systems activated and deactivated to see the effect more clearly and for longer time period with different driving conditions.

Action Result(s) Bus Start End

Putting up the data collection Back office ready to receive and store 1/2016 10/2016 system (back office) data Terminal ready for reading CAN data Vehicle terminal installation eMULE 10/2016 11/2016 and sending it to back office Planning of the energy saving Energy saving strategies eMULE 10/2016 2/2017 strategy with simulations Testing of the strategies in the Verified (laboratory) energy saving eMULE 1/2017 2/2017 laboratory on a dynamometer strategies

12R.1 Energy strategies inactive Reference driving (“NO EBSF_2”) 12R.2 11/2016 9/2017 13M Energy strategies activated driving Energy strategies active 4/2017 9/2017 (“EBSF_2” status) Intermediate analyses and Intermediate data analysed and report- all 4/2017 9/2017 report ed Writing of execution report Deliverable D8.2 all 9/2017

Final analyses All data analysed all 10/2017 4/2018

Final reporting Deliverable D8.3 all 4/2018 Table 4. Action list and timing for TIHEL1: ADAPTAUX

Deliverable 8.1 Page 26 of 32 Action Result(s) Bus Start End

Putting up the data collection Back office ready to receive and store 1/2016 10/2016 system (back office) data Terminal ready for reading CAN data and Vehicle terminal installation eMule 10/2016 11/2016 sending it to back office Data collection and speed profile Collection of operation data and speed eMule 11/2016 12/2016 generation tests profile generation works Linkker Vehicle terminal installation Data collection active 11/2016 12/2016 12R.1 Linkker Vehicle terminal installation Data collection active 11/2016 12/2016 12R.2 Vehicle terminal installation Data collection active Linkker 13 11/2016 12/2016 12R1, Guiding system inactive Reference driving 12/2016 9/2017 12R2 Data analysation for optimal 12R1, Initial version of optimal speed profile 12/2016 2/2017 speed profile 12R2 Guiding system testing en-route, Guiding works eMULE 1/2017 3/2017 no passengers 12R1, Guiding system inactive Reference driving (“NO EBSF_2”) 2/2017 9/2017 12R2 12R1, Guiding system active Guided driving (“EBSF_2” status) 4/2017 9/2017 12R2 Intermediate analyses and report Intermediate data analysed and reported all 4/2017 9/2017

Writing of execution report Deliverable D8.2 all 9/2017

Final analyses All data analysed all 10/2017 4/2018

Final reporting Deliverable D8.3 all 4/2018 Table 5. Action list and timing for TIHEL2: EDRIVEAID

Deliverable 8.1 Page 27 of 32 6.2 Demo team The functions and roles of various persons in the demo team with their contact information are presented in Table 6.

Company and Function/Role Person contact information

Sub-project Dr. JUHANI LAURIKKO, VTT, [email protected] Leader, TRA1 Principal Scientist Mr. PEKKA RAHKOLA, Demo leader VTT, [email protected] Research Scientist Mrs. MIKAELA RANTA, Simulations VTT, [email protected] Research Scientist TI implementation, Mrs. Paula Silvonen, VTT, [email protected] validation Research Scientist MR. ARI-PEKKA PELLIKKA, Data collection VTT, [email protected] Research Engineer MR. SAMI RUOTSALAINEN, Linkker, Bus manufacturer CEO, Linkker [email protected] MR. AKU TUOKILA Transdev Finland Oy, Bus operator Service Engineer [email protected] Table 6. Functions and roles of persons in the demo team with contact information

Deliverable 8.1 Page 28 of 32 7 Partner Contribution

Company Section(s) Description of the partner’s contribution VTT all Writing of the report Transdev Finland 5 Checking the accuracy of the operation data Linkker 5 Checking the accuracy of the bus data UITP all Quality check

Deliverable 8.1 Page 29 of 32 8 Conclusions

The main objectives of the demonstration are to increase the attractiveness of public bus transport service by improving the accuracy and the riding comfort of the service and at the same time to improve the economic performance of the operator by lowering the energy consumption of the bus operations. In the demonstration in Helsinki Metropolitan area two new technological innovations for full-electric busses are studied as a tool to- wards the main objectives of the EBSF_2 project. The first technical innovation, ADAPTAUX (TIHel1), demonstrates an optimised use of auxiliary devices. The starting point is to optimise the energy consumption of the hydraulic pump of the power steering by switching the pump off when power steering is not needed, and air compressor by activating it during regenerative brakings and feeding the regenerated energy directly to the air compressor without storing it to the battery. The potential of these approaches were tested using a calculation model of the energy usage with a real operation data, and found to be 2-3 % of the total energy consumption. The second technical innovation, EDRIVEAID (TIHel2), demonstrates the use of an intelligent and adaptive driver assistance system to help the driver to drive more energy efficiently while maintaining passenger comfort and service quality. The system provides a real-time guidance to drivers, taking into account vehicle en-route position compared to scheduled position, speed limit and the travelling comfort regarding the intensity of accelerations and decelerations. This kind of approach was implemented and tested on diesel buses giving a saving potential of 5-10 %. In this demonstrator the system is developed further and applied to fully electric buses. In Helsili/Espoo demonstrator the potential of these technical innovations will be evaluat- ed and validated in real operational scenarios, according to the demo plan detailed in sec- tion 6.1, to give impact on development of efficient solutions to both citizens and bus stakeholders’ needs.

Deliverable 8.1 Page 30 of 32 9 References

[1] Erkkilä, K., et.al. Energy Efficient and Intelligent Heavy Vehicle – HDENIQ – Final Report. VTT Technical Research Centre of Finland, 2013. VTT-R-08344-12. 139 p. [2] Laurikko, J., et.al. Electric city bus and infrastructure demonstration environment in Espoo. The 28th International Electric Vehicle Symposium and Exhibition, EVS28, Kintex, Gouang, Korea, 3-6 May, 2015. 11 p. [3] Halmeaho, T., et.al. Advanced driver aid system for energy efficient electric bus operation. 1st International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2015, Lisbon, Portugal, 20 - 22 May, 2015. 6 p.

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