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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