eBus Simulator
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Presentation Overview
1. About New Flyer Industries and Xcelsior
2. Project Goals
3. Data Requirements
4. Development Environment and Risks
5. Validation Method
6. Milestones and Presentation Venue
About New Flyer
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Founded in 1930, North America’s Transit Bus leader in technology and innovation: Approx 52% of fleet of HD buses in operation are NF/NABI/Orion Approx 50% heavy-duty bus delivered market share annually Approx 34% aftermarkets parts market share
3,400 employees, with 2/3 located in the US
HD buses offered in 35’, 40’ and 60’ articulated. MiDi offered in 30’and 35’. Tested to all required HD transit standards and more. Penn State Altoona, Exova, etc.
Only NA Bus OEM with operating systems meeting three ISO Certifications:
ISO9001: Quality Management System ISO14001: Environmental Management ISO18001: Occupational Health and Safety
Publicly traded on TSX. Well capitalized, low leverage. Marcopolo S.A. is the largest shareholder (19.99%)
New Flyer OverviewLeader in Volume, Technology, Innovation, Parts and Support
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Natural Gas
Clean Diesel
Hybrid-Electric
Battery-Electric
Electric-Trolley
Market Leadership in Propulsion Technology
New Flyer’s battery-electric Xcelsior®
Pilot bus testing complete and in service. 2 electric buses delivered to Chicago in Q2-14 4 buses delivered to Winnipeg in Q4-14 Electri60’ artic in development
Single platform - multiple propulsion options
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Pantograph by Schunk– not New Flyer proprietary
Single Pantograph
Conductive Charge System
Project Goals
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Difficulties Associated With Electric Propulsion
Limited range increases complexities associated with operations and planning
Optimization of charge infrastructure location
HVAC and other onboard systems have a material impact on power consumption making local weather an important factor
No prescribed methodology for assessing performance with respect to a given application
Performance of the complete system constitutes a significant portion of the evaluation criteria
Crowded space with numerous customers making unsubstantiated performance claims
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What is the eBus Simulator?
“The eBus Simulator is a web-based GIS software application, designed to enhance understanding of New Flyer™ Xcelsior® electric bus performance, with respect to the unique environment of individual customers.”
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Allow for better understanding of suitability of the New Flyer electric bus platform for a given customer specific scenario
Provide New Flyer with a model which can be used to address customer concerns or challenge competitor claims regarding Xcelsior performance
Increases comfort level around selected battery capacity and help reduce tendency to increase price due to excessive conservatism
Create greater customer confidence regarding New Flyer electric bus performance claims
What will eBus Simulator Provide?
Confidential Best Bus Value and Support for Life.11
What Values Will Simulation Reports Produce?
Propulsion HVAC Accessory “Hotel” Loads
Power Consumed kWh Power Created in kWh
(Regenerative braking)
Average Ambient Temperature Hourly Weather Forecast Chart Target Interior Temperature Hours of AC Operation Hours of Heat Operation Power Consumed in kWh
Lighting Power Consumption in kWh
All other Accessory Power Consumed in kWh
Battery Statistics Vehicle Statistics
Total Charge Time from Conductive Charging Total Charge from Conductive Charging in
kWh Time Elapsed During Charging Total Discharge Battery Charge Cycles
Elapsed Operating Time Distance Traveled Distance Traveled at Various Grades Average Speed Number of Stops
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Complex / Multivariate Generally Linear
Traction Motors HVAC “Hotel” Loads
Bus Stops Road Grade Rate of Acceleration
(Driver Behavior) Posted Speed Limits
Ambient Temperature Target Interior
Temperature Dwell Time
APC Systems Camera Systems Lighting NSAS All Other Onboard
Electronics
Other
Charge Station Location Charge Station Type (kWh) Garage Location
Generally Univariate
What Variables Must Be Accounted For?
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Simple tool, designed in response to a request from Engineering
Approximately 2,000 lines of JavaScript, HTML & CSS code
Determines vehicle range based upon Penn State Altoona Test performance, hourly weather forecast, battery capacity
Takes into account power consumption from propulsion and HVAC
Custom “Time Dilator” JavaScript object and other design considerations allow for future capability to be added
While useful, the existing range simulator is a simple tool. A more complex software application is required in order to account for the unique requirements of each individual customer.
Built from Existing Altoona Range Simulator
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eBus Simulator development version with GIS integration. Sample data loaded for Chicago area.
Developmental Version with OSM Integration
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Sample elevation data for the Dallas area. Note the floodway in the upper-right corner.
Developmental Version with Elevation Integration
Project Data Requirements
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LiDAR or other elevation data provided by the USGS. Minimum accuracy of 1/9 - 1/3 arc second (3-10m)
Customer provided route layers Routes Bus Stops Posted Speed Limits
Other Relevant Data Proposed Conductive Charge Station Location Garage Location Depot Charging Local Weather Conditions
Data Requirements
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Elev
ation
Retu
rn T
ype
1. Location - Where are we?
2. Elevation - How high is the point above mean sea level (MSL)?
3. Return type - What type of surface are we looking at?
-Buildings, Roadways, Foliage
These three elements allow us to determine road grade, which is critical for accurately modeling power consumption from propulsion as well as power recovered during regenerative braking.
*Above LiDAR images are New Flyer renderings of San Francisco, California with USGS provided data.
What do LiDAR Data Provide?
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When HVAC or Heat power is 10 kW, Range is reduced 25%
HVAC energy required at 95F ambient is 10 kW with doors opening on CBD cycle
Maintenance Heat at 40°F is about 10 kW with doors opening on CBD cycle
Maintenance Heat at 10°F is about 20 kW. Optional diesel heating recommended
Effect of Weather on Power ConsumptionWhy Account For Local Weather?
Project Platform & Risks
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Programming Language(s) Other Libraries and APIs GIS Layer Development JavaScript PHP Python SQL
Google Charts jQuery 2.1 jQuery UI OpenLayers 3.5
QGIS Geospatial Data Abstraction
Library (GDAL)
Development Environment
eBus Simulator uses an array of common programming languages and tools which are well-suited to produce rich, standards compliant, cross-platform web applications. All operating systems, libraries and applications are freely available and open source with the exception of the Google Charts API.
Operating System Web Server / Services GIS Stack
Ubuntu Server 14.04 LTS (Linux) on Amazon EC2
Apache 2.4 Tomcat Node.js
GeoServer PostGIS Extension Geospatial Data Abstraction
Library (GDAL)
Programming
Server
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Risk Severity Mitigation StrategyDevelopment of method to determine roadway grade from LiDAR and other elevation data
Medium None – Removal of Feature
Slow code execution due to limited support for parallelism in JavaScript
Medium Implementation of “Event Pool” strategy, extensive preprocessing and well-written non-blocking source code
Access to necessary vehicle performance data Low Early communication with Engineering, use of Connect Telematics
Project Risks
A recent study on rural roads was able to determine road grade with a mean absolute difference of 0.53% despite the fact that 94% of LiDAR points were dropped due to classification as foliage.
Validation Method
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Main Control Unit (MBU) I/O discrete and analog 2 x J1939 + 1 x J1708 3-Axis Accelerometer Expandable in number of I/O, interfaces ,such as J1939, J1708, RS485,
RS232, memory SD card and transfer data back over Wi-Fi Updated over-the-air
GSM Modem and GPS GPS module and antenna GSM modem and antenna Easy to migrate to other
technologies
$500,000 - $1,000,000Remote Sensing Device
Connect: On-Board Components
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Energy Storage System
Traction Motors
HVAC System
Door Actuators
Infrared Passenger Counting Sensors
Integrated Network of Complex Subsystems
Transit buses represent a complex assemblage of intelligent, networked hardware.
Conductive Charging
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Connect: Opportunistic Harvesting of Data from CAN
New Flyer Connect is capable of opportunistically harvesting thousands of pieces of information exchanged through the Controller Area Network (CAN Bus). Through these data, an array of complex polynomial functions will be generated to describe vehicle behavior. As new data are created, constant validation will occur.
Milestones and Presentation Venue
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Requirement DateSubmit Abstract September 9, 2015Submit Technical Paper April 22, 2016Presentation May 15th – 18th 2016
American Public Transit Association Presentation
Project Milestones Phase I – Demonstrate Key Technologies
Deploy new server instance (complete) Demonstrate integration of core UI elements and
communication with GeoServer (complete) Update TimeDilator Library for ease of programming
(complete) Acquire necessary data from strategic customer
(complete) Phase II – Initial Route Modeling
Model power consumption taking into account unique customer route profile
Develop underlying web-services necessary to UI and load layers based upon user input.
Phase III – Integration of Elevation Data Demonstrate method for determining road grade from
elevation data and assigning to vector layers Phase IV – Complete Reporting Module
Simulation reports reviewed and approved by Technical / Field Sales
Conduct and present analysis for unnamed strategic customer
American Public Transit Association (APTA)2016 Bus and Paratransit Conference
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