autonomous vehicles & electro-mobility

Energy Research Institute @ NTU (ERI@N) 1 CleanTech Loop, #06-04 CleanTech One, Singapore 637151 Phone: (65) 6592 1786 / 2468 Fax: (65) 6694 6217

Autonomous Vehicles & Electro-Mobility

Energy Smart, Research Innovation

* 2

Contents

• Key Members

• Areas of Focus

• Key Ongoing Projects

• Equipment & Facilities

– Lab Test platform

– Field test platform

• Summary

* 3

Key Members & Resources

Resources : 3 PhD students; 2 RF, 5 RA, 2 RE, 2 PO ~100 sqm. Drive Train ~200 sqm. AV Test and Simulations Lab

Satyajit Athlekar

Prof Ng Heong Wah

Assoc Professor (MAE)

Prof Arvind Easwaran Asst Prof (CSE)

Prof Ali Maswood Assoc Prof (EEE)

Prof Wang Youyi Prof (EEE) Niels De Boer

Senior Scientist

Anshuman Tripathi

Senior Scientist

Li Yang

Research Fellow Research Associate

Power systems Power Electronics Energy storage Sensors & actuators

Autonomous Vehicles Mechanical Systems Automotive designs

Autonomous Vehicles Regulations Power system Components

Electro-magnetics Sensors designs Simulations

Energy Storage System Integration Project Management

Automation & Controls Control & processors Robotics

Senior Research Fellow

Senior Scientist

Kei Leong HO

V Sriram

Senior Research Fellow

Power Electronics EMC-EMI designs Sensor designs Power Systems

Start-ups Business development

Cao Shu Yu

* Project Partnerships

• System integration (NRF)

• Grid integration (EMA) • Transport (LTA,MOT)

• First Prototype vehicle • Charging equipment • Renowned expertise in

a technical area

NTU(ERI@N)

Local Collaborator/

Agency

• RD & D • Prototype and test bedding • Knowledge base • IP

Industry

* Background & Opportunity

Towards sustainable mobility system

Campuses

Singapore

Leisure

Food places

Housing

Work- places

NTU : An ideal sample size

Cluster: NTU

Cluster NTU

CBD

Theme Park

Science

park

Cam-pus

* 6

Microcosm of NTU Campus

p u b l i c

s h u t t l e

• Long waiting time • Packed buses • Non-operational

during weekends and holidays

$$$

• Long waiting time

• Packed buses • Non 24/7

services

Hilly terrain

Warm, humid

weather

* 7

JTC CleanTech

Park

NTU Campus

7

Microcosm Map of NTU Campus

o Academic Buildings & Research

Institutes

o Student/staff Halls & Housings

o Parks, Sports & Recreational Facilities

o Commercial Buildings

o Canteens, Cafeterias & Restaurants

* 8

First/Last mile transport for public and logistics

RD&D Focus: AVEM

* 9

First/Last mile transport @ NTU, Mobility on

demand

* Summary of Ongoing Projects (Test-bedding in NTU,

deployment in Campus & other sites)

10

Serial Number

Project Title Project Timeline

1 Flash charging of Port AGVs SMI/PSA Jan 2016 – July 2018

3 AV buggies @ Sentosa iDA/YHI/Ai Robotics March 2016 – Nov 2016

6 Autonomous Buses (RFI) LTA/SMRT Aug 2016-July 2020

9 Center of Excellence for Autonomous Vehicles LTA/JTC July 2016 ---

* Robotics kit for a Bus & Validation @ SMRT

Woodlands depot

Design of robotics kit for conversion

Time-lines

Simulating & testing in a given environment

* 12

Front Sensors

Rear sensors

Auto Steer

Wheel and Drive control

Subjecting tests for vehicle turning

Traffic signal and braking Traffic Aware Maneuvering

Traffic Negotiations

Adaptive Speed Control and Emergency braking

Challenge ahead – AutoBus Operation for real-time

scenarios 12

* Objectives

Continuous 24/7 operation : No dedicated charging time

Minimum on-board energy storage : Light weight, Efficient, Less

than 1/20 th of the existing numbers

Zero Carbon Emission : 100 % electric

Long lifetime of onboard energy storage : Super-cap interfaces

Minimal Grid impact : Internet of energy concepts, Real time grid

interaction

Real time solar integration : For seamless operation in a campus

and beyond

* Research & Development

• Modeling of Grid connectivity dynamics with multiple flash charging stations acting in real time

• Real time interaction of flash charging stations and EVs through dynamic intermodal connectivity : Internet of energy models

• Flash charging methods and charging strategies

Charging

• Compact on-board hybrid energy storage (Existing Supercap + Batteries, New Super-caps + batteries)

• High energy density grid to charging station buffer

Storage

• High power density power electronics, High energy density storage; compact “invisible” charging stations

• Design to validation for electrical, mechanical and thermal packaging

Packaging Demo/Test-bed

* Phase I : Test Route

Research Techno

Plaza

Clean Tech Park

Station

*

2016 2018 2017

Conceptualization, design, validation

Electrical, thermal and mechanical packaging

Demonstration

Grid connectivity studies and Charging station design with solar integration

Design of Hybrid energy storage

Flash Charging

Grid-connectivity with

multiple charging

stations

Supercapacitor based

charging stations

Hybrid energy storage

Energy Management

system (IoE concepts)

Renewable integration

with Energy buffer

Compact design

Packaging to

adapt tropical

conditions

Test-Bed in NTU

campus & data

collection

Storage Packaging/Demonstration

Technology development timeline

Energy Research Institute @ NTU (ERI@N) 1 Clean Tech Loop, #06-04 Clean Tech One, Singapore 637151 Phone: (65) 6592 1786 / 2468 Fax: (65) 6694 6217

Electric Vehicles potential impact on

distribution grid

* 18

Singapore’s fleets 65% Cars in 2014

Vehicle population

in total numbers

Share of fleets (2014)

Source: LTA

LGVs: Light Goods Vehicles

HGVs: Heavy Goods Vehicles

VHGs: Very Heavy Goods Vehicles

GVPs: Goods Passengers Vehicles

17%

15%

3% 1% 1% Cars

Goods Vehicles

Motorcycles

Taxis

Private buses

Public buses65%

616,609

144,404 92,731

32,196 28,736 16,712 12,353 4,756 2,868

* 19

Penetration

Scenarios

Single phase 3.3kW Charger

- Transformer loading MVA

Year LS MS HS LS MS HS

2015 0 0 0 0 0 0

2020 30 91 152 0.099 0.3003 0.5016

2025 49 147 245 0.1617 0.4851 0.8085

2030 73 220 367 0.2409 0.726 1.2111

2040 122 367 612 0.4026 1.2111 2.0196

2050 171 514 857 0.5643 1.6962 2.8281

19

Transformer MVA loading due to Single phase 3.3 kW, 7.4 kW, three phase 3.3 kW, 10 kW, 22 kW, 43 kW and DC 50 kW , 120 kW charger penetration

Transformer loading obtained by multiplying the kW rating of the charger and the number of vehicles per penetration scenario

GPVs: BEVs-Singapore level, Concentrated

Loading

Penetration Scenarios

Single phase 7.4 kW Charger

- Transformer loading MVA


2015 0 0 0 0 0 0

2020 30 91 152 0.222 0.6734 1.1248

2025 49 147 245 0.3626 1.0878 1.813

2030 73 220 367 0.5402 1.628 2.7158

2040 122 367 612 0.9028 2.7158 4.5288

2050 171 514 857 1.2654 3.8036 6.3418

Three phase 10 kW

Three phase 22 kW Three phase 43 kW

Year LS MS HS LS MS HS LS MS HS LS MS HS

2015 0 0 0 0 0 0 0 0 0 0 0 0

2020 30 91 152 0.3 0.91 1.52 0.66 2.002 3.344 1.29 3.913 6.536

2025 49 147 245 0.49 1.47 2.45 1.078 3.234 5.39 2.107 6.321 10.535

2030 73 220 367 0.73 2.2 3.67 1.606 4.84 8.074 3.139 9.46 15.781

2040 122 367 612 1.22 3.67 6.12 2.684 8.074 13.464 5.246 15.781 26.316

2050 171 514 857 1.71 5.14 8.57 3.762 11.308 18.854 7.353 22.102 36.851

Direct current 50 kW


Year LS MS HS LS MS HS LS MS HS

2015 0 0 0 0 0 0 0 0 0

2020 30 91 152 1.5 4.55 7.6 3.6 10.92 18.24

2025 49 147 245 2.45 7.35 12.25 5.88 17.64 29.4

2030 73 220 367 3.65 11 18.35 8.76 26.4 44.04

2040 122 367 612 6.1 18.35 30.6 14.64 44.04 73.44

2050 171 514 857 8.55 25.7 42.85 20.52 61.68 102.84

> 1 MVA loading >10 MVA loading > 100 MVA loading DT overloading clearly observed in the Hypothetical case

studied to get a directional feel.

* 20

GPVs: BEVs- Singapore level, Concentrated

Loading

20

Single phase 3.3 kW charger penetration based DT MVA loading Single phase 7.4 kW charger penetration based DT MVA loading

Three phase 10 kW charger penetration based DT MVA loading DC 50 kW charger penetration based DT MVA loading

MV

A

MV

A

MV

A

MV

A

The intersection of the red line with the bar chart shows the limitation of DT

DT overloading clearly observed in the Hypothetical case studied to get a directional feel.

* 21

GPVs: BEVs District level, Concentrated

Loading 22 kV DTs in Singapore district wise – rough estimate

Number of districts in Singapore 28

Number of 22 kV substations 5869

Number of 6.6 kV substations 4810

No of 22 kV substation per district 209.61

Impact of EV penetration

LS Ok

MS need to calculate

HS need to calculate

DT in Singapore district wise

Penetration scenarios evenly spread across 28 districts

Singapore level District level


2015 0 0 0 0 0 0

2020 30 91 152 1.07 3.25 5.4285714

2025 49 147 245 1.75 5.25 8.75

2030 73 220 367 2.61 7.857 13.107143

2040 122 367 612 4.36 13.11 21.857143

2050 171 514 857 6.11 18.36 30.607143

EV penetration scenarios for districts evenly distributed

Single phase 3.3 kW Single phase 7.4 kW

Year LS MS HS LS MS HS LS HS

2015 0 0 0 0 0 0 0 0

2020 1.0714286 3.25 5.42857143 0.003535714 0.010725 0.0179 0.007928571 0.040171

2025 1.75 5.25 8.75 0.005775 0.017325 0.0289 0.01295 0.06475

2030 2.6071429 7.857142857 13.1071429 0.008603571 0.025928571 0.0433 0.019292857 0.096993

2040 4.3571429 13.10714286 21.8571429 0.014378571 0.043253571 0.0721 0.032242857 0.161743

2050 6.1071429 18.35714286 30.6071429 0.020153571 0.060578571 0.101 0.045192857 0.226493

Transformer loading due to 1 phase chargers penetration

The overall estimated EV penetration scenario have been assumed roughly to be evenly spread across the 28 districts of Singapore. The total number of DTs have also been roughly spread out evenly across each of the district.

No DT overloading observed in the case for GPVs in Single phase charger study. Only 22 kV DTs considered

* 22

GPVs: BEVs District level, Concentrated Loading

Three phase 43 kW Direct current 50 kW Direct current 120 kW


2015 0 0 0 0 0 0 0 0 0 0 0 0

2020 1.0714286 3.25 5.42857143 0.046 0.1398 0.2334 0.05 0.163 0.2714286 0.129 0.39 0.6514286

2025 1.75 5.25 8.75 0.075 0.2258 0.3763 0.09 0.263 0.4375 0.21 0.63 1.05

2030 2.6071429 7.857142857 13.1071429 0.112 0.3379 0.5636 0.13 0.393 0.6553571 0.313 0.943 1.5728571

2040 4.3571429 13.10714286 21.8571429 0.187 0.5636 0.9399 0.22 0.655 1.0928571 0.523 1.573 2.6228571

2050 6.1071429 18.35714286 30.6071429 0.263 0.7894 1.3161 0.31 0.918 1.5303571 0.733 2.203 3.6728571



2015 0 0 0 0 0 0 0 0 0

2020 1.0714286 3.25 5.42857143 0.01 0.0325 0.054286 0.023571429 0.0715 0.1194286

2025 1.75 5.25 8.75 0.02 0.0525 0.0875 0.0385 0.1155 0.1925

2030 2.6071429 7.857142857 13.1071429 0.03 0.078571429 0.131071 0.057357143 0.1729 0.2883571

2040 4.3571429 13.10714286 21.8571429 0.04 0.131071429 0.218571 0.095857143 0.2884 0.4808571

2050 6.1071429 18.35714286 30.6071429 0.06 0.183571429 0.306071 0.134357143 0.4039 0.6733571

> 1 MVA loading >10 MVA loading > 100 MVA loading DT overloading observed in the case for GPVs in Three phase charger

and DC 50 kW and 120 kW study. Only 22 kV DTs considered

Population (units) 2015 2020 2030 2050

Scenario 3 979,354 983,567 989,094 992,440

BEVs and PHEVs

2015 2020 2030 2050

Low Med High Low Med High Low Med High

BEVs (#) 80 19,166 47,405 75,643 57,270 142,449 227,628 134,012 333,133 532,255

BEVs (%) 0% 2% 5% 8% 6% 14% 23% 14% 34% 54%

PHEVs (#) 100 9,729 15,923 22,005 17,685 36,403 54,756 33,469 77,256 120,174

PHEVs (%) 0% 1% 2% 2% 2% 4% 6% 3% 8% 12%

Energy Demand (GWh)

2015 2020 2030 2050


BEVs 0 117 313 510 323 874 1,425 622 1,682 2,741

PHEVs 0 19 51 76 52 142 212 99 272 406

Sum 0 136 364 586 375 1,016 1,637 721 1,954 3,147

All vehicles in Singapore and EV penetration scenario

The EV penetration is estimated to be about 50 % of the overall private car population right now and for other vehicles different estimations have been arrived at based on NTU study

* 24

2015 2020 2030 2050

Population (units) 624,936 623,997 622,441 619,956

BEVs and PHEVs

2015 2020 2030 2050


BEVs (#) 80 8,914 26,743 44,571 26,676 80,028 133,380 61,996 185,987 309,978

BEVs (%) 0% 1% 4% 7% 4% 13% 21% 10% 30% 50%

PHEVs (#) 100 8,783 13,240 17,697 16,215 29,553 42,891 30,998 61,996 92,993

PHEVs (%) 0% 1% 2% 3% 3% 5% 7% 5% 10% 15%

Energy Demand (GWh)

2015 2020 2030 2050


BEVs 0 31 93 156 84 253 421 160 481 801

PHEVs 0 10 19.00 29 26 52 78 49 99 148

Sum 0 41 112 185 110 305 499 209 580 949

Private vehicles (cars) in Singapore

The EV penetration is estimated to be about 50 % of the overall private car population right now

* 25

Private Cars: BEVs-District level, Distributed

Loading Single phase 3.3 kW


2015 2.8571429 2.857142857 2.85714286 4.49821E-05 4.49821E-05 4.49821E-05

2020 318.35714 955.1071429 1591.82143 0.005012132 0.015036957 0.02506122

2030 952.71429 2858.142857 4763.57143 0.014999284 0.044997853 0.074996422

2050 2214.1429 6642.392857 11070.6429 0.034858886 0.104576095 0.174293304

Single phase 7.4 kW Three phase 10 kW

Year LS MS HS LS HS LS MS HS

2015 2.8571429 2.857142857 2.85714286 0.000100869 0.000101 0

0.000136309 0.000136

2020 318.35714 955.1071429 1591.82143 0.011239325 0.056198 0.02

0.045566536 0.075943

2030 952.71429 2858.142857 4763.57143 0.033634759 0.168174 0.05

0.136357131 0.227262

2050 2214.1429 6642.392857 11070.6429 0.07816841 0.39084 0.11

0.316897257 0.528162



2015 2.8571429 2.857142857 2.85714286 0.000299881 0.0003 0.0002999 0.0006 0.0006 0.0006

2020 318.35714 955.1071429 1591.82143 0.03341421 0.1002 0.1670748 0.0653 0.1959 0.3266

2030 952.71429 2858.142857 4763.57143 0.099995229 0.3 0.4999761 0.1954 0.5863 0.9772

2050 2214.1429 6642.392857 11070.6429 0.232392571 0.6972 1.1619554 0.4542 1.3627 2.2711




2015 2.8571429 2.857142857 2.85714286 0 0.0007 0.0006815 0.002 0.002 0.0016357

2020 318.35714 955.1071429 1591.82143 0.08 0.2278 0.3797155 0.182 0.547 0.9113171

2030 952.71429 2858.142857 4763.57143 0.23 0.6818 1.1363094 0.545 1.636 2.7271426

2050 2214.1429 6642.392857 11070.6429 0.53 1.5845 2.6408076 1.268 3.803 6.3379383

LS - Low penetration scenario; MS - Medium penetration scenario; HS- High penetration scenario

> 1 MVA loading >10 MVA loading > 100 MVA loading

The number in the colored boxes show the actual number of distribution transformers in Singapore which will be overloaded in relation to the EV penetration under distributed loading

DT overloading observed in the case for Cars in Three phase charger study at 22 kW and 43 kW and also for DC 50 kW and 120 kW. Only 22 kV DTs considered

* 26

Private Cars: BEVs-District level,

Concentrated Load Single phase 7.4 kW Three phase 10 kW


2015 2.86 2.86 2.86 0.02 0.02 0.02 0.03 0.03 0.03

2020 318.36 955.11 1591.82 2.36 7.07 11.78 3.18 9.55 15.92

2030 952.71 2858.14 4763.57 7.05 21.15 35.25 9.53 28.58 47.64

2050 2214.14 6642.39 11070.64 16.38 49.15 81.92

22.14 66.42 110.71

Single phase 3.3 kW


2015 2.86 2.86 2.86 0.01 0.01 0.01

2020 318.36 955.11 1591.82 1.05 3.15 5.25

2030 952.71 2858.14 4763.57 3.14 9.43 15.72

2050 2214.14 6642.39 11070.64 7.31 21.92 36.53



2015 2.86 2.86 2.86 0.06 0.06 0.06 0.12 0.12 0.12

2020 318.36 955.11 1591.82 7.00 21.01 35.02 13.69 41.07 68.45

2030 952.71 2858.14 4763.57 20.96 62.88 104.80 40.97 122.90 204.83

2050 2214.14 6642.39 11070.64 48.71 146.13 243.55 95.21 285.62 476.04

Three phase 43 kW Direct current 50 kW



2015 2.86 2.86 2.86 0.12 0.12 0.12 0.14 0.14 0.14 0.34 0.34 0.34

2020 318.36 955.11 1591.82 13.69 41.07 68.45 15.92 47.76 79.59 38.20 114.6 191.02

2030 952.71 2858.14 4763.57 40.97 122.90 204.83 47.64 142.91 238.18 114.3 342.9 571.63

2050 2214.14 6642.39 11070.64 95.21 285.62 476.04 110.71 332.12 553.53 265.7 797.0 1328.48

> 1 MVA loading >100 MVA loading

The number in the colored boxes show the actual number of distribution transformers in Singapore which will be overloaded in relation to the EV penetration

DT overloading clearly observed in the case for Cars in all type charger study starting at Level 1, Level 2 and Level 3 type of chargers. Only 22 kV DTs considered

If the assumption that all cars charge at same time is not considered, high power chargers may still not hit the peak capacity available, but the intermittency and harmonics injections may still lead to power quality issues.

* Vehicle Power train test lab

Challenges Addressed:

• Test vehicle “prototype” for real road

conditions

• “Autonomous Vehicle” intelligence kit

design

• “V2G concepts” and Propulsion

“Energy Management”

Key Outcome/Deliverables:

• Performance analysis of Zinc-air battery

• Energy management system for Zn-air

and Li-ion

• Design and validation of robotics kit for

vehicles

• Flywheel energy storage management

Energy

Storage ESS

1

ES

S2

ESS

1

ES

S2

ES

S3

* 28 Flywheel applied to photovoltaic power

Algorithm:

• Smooth solar production

• peaks and troughs detection

• Flywheel Charge or discharge

to smooth production

Results:

• Reducing of the photovoltaic

production variation

• Variation averages =

10% before to 5% with flywheel

Photovoltaic:

• 1000 m2, 13 kW

Flywheel:

• 15000 rt/min, η = 85-90%

• Short Storage = 10-15 mins

* 29 Current Challenge – Hybrid battery for

vehicle traction

Starting

Acceleration + Uphill

Cruising

Braking and decelerating

Stopped

ESS 1

ESS 2

Motor

ESS 1

ESS 2

Motor ESS 1

ESS 2

Motor

ESS 1

ESS 2

Motor ESS 1

ESS 2

Motor

* Equipment & Facilities

Partner DLRE

Lab Test Platform

Car support mechanism for lifting

and locking

Alignment system for Generators

Generator – hub coupling system

*

Inverter

to Grid

Innovation Approach – Plant model using

Matlab® and dSPACE® Control desk 31

Absolute

Position sensor -

Encoder

Interface

Board

Load current

and voltage

dSPACE

controller

DS 2202 A/D card

Vehicle

Inverter

ESS 1

ESS 2

Control

signals

Vehicle Model

Common

DC bus

Rectifier

for each

PM

generator

POWER

CABINET

* Hardware-in-the-loop testing

Supervisory controls for the vehicle operation

implemented in simulation environment

Lab and Test bed set-up 32

Generators coupled to the rear wheel axle

Real road conditions emulated using

generator as a load

* Scalable for

diverse range

of applications

(50-500 kW

Vehicle Power train test lab – Total system solution 33

Boat Drive train

Drive train of

buses

Integrated

solution for

component

sizing,

performance &

system control

tuning

Auto-bus

operation test

Integration to

bus simulator

Energy Research Institute @ NTU (ERI@N)

1 CleanTech Loop, #06-04 CleanTech One, Singapore

637151

Phone: (65) 6592 1786 / 2468 Fax: (65) 6694 6217

High Power Density Energy Storage Solution for Stationary &

Mobile Applications

* High Power Density Energy Storage Solution for Stationary & Mobile Applications

35


• Thermal management of battery pack

• Demonstration of fast charging and fast discharging

Key Outcomes/Deliverables:

• Design of battery pack, BMS & thermal enclosure.

• Thermal analysis, structural assessment, fast charging and

discharging tests.

40% size reduction

Increased power density

Sustained temperature at 25°C

Enhanced battery life by >30%

Air Cooled

Liquid Cooled

* 36

Mechanical & Thermal

Design

Concept Electrical

Design

Enclosure Fabrication

Hardware Tests

BMS Integration

Innovation Approach

* Latest Findings 37

Source: NREL Battery thermal modelling and testing

Thermal Management Impact on Battery Life:

Battery capacity of 80% for more than 9

years

Increased lifespan of 2 years compared to

air cooling

Average Battery Temperature – Charging at 1.4C & 2C Average Battery Temperature – Discharging at 1.4C & 2C

* 38 Future Scope

Proof of Concept

Proof of Value

Deployment

Progress

Energy Storage & Charging Station

Integration & Demonstration

Deployment Plan:

1. Bollore – Flash charging electric busses @ NTU Campus By Q3 2017

2. SMI Grant Call – Port cargo handling equipment & charging stations By Q2 2018

3. PSA – Scaling up, field testing & deployment @ PSA Terminal By Q4 2019

Energy Research Institute @ NTU (ERI@N) 1 CleanTech Loop, #06-04 CleanTech One, Singapore 637151 Phone: (65) 6592 1786 / 2468 Fax: (65) 6694 6217

Shared Personal Mobility Solution

Smart e-Bikes Sharing Service @ NTU

* Shared Personal Mobility Solution

40

Our Team


• Tackle First mile, Last mile issue

• Provide an alternative transportation model

for personal and small groups of users

• Encourage active & healthy lifestyle

Key Outcome/Deliverables:

• Develop a sustainable Business Model

• Deployment of >20 e-bikes inside campus by

June 2016

• Deployment of >100 e-bikes inside campus by

Q1, 2017

*

41

Innovative Approach Need for Shared Personal Mobility Solution

Photovoltaic Charging Station

*for illustrations only

Experimental Research Project using objects

with electric-assistance

Convenient resource booking via smartphone

Maximize resource utilization capability via

sharing

Sustainable charging means via solar powered

recharge stations

Motor

Battery Control for

electric assistance

Smart Device

• Fleet Management • Real-time Monitoring • Battery SOC • Geo-fencing

Data Analytics

Convenient Booking

Range: 70 km/charge

*

Heat map of Least Accessible Areas in NTU Campus

42

Key Findings

Greenfest 2016

JTC

CleanTech

Park

Sample of Vehicle Tracking in Campus

NTU Sports

Recreational

Centre

NTU

Academic

Buildings

*

43

Future Impact

p u b l i c

s h u t t l e

V2V, V2X possibilities – Cars, Motorcycles, AVs, Bicycles, kick-scooters, etc

Scalable Deployment >100 e-bikes inside campus by Q1, 2017

Future Deployment

NTU, CleanTech Pack, Bulim and Tengah industrial estates

+

Proposal for SMI Maritime Sustainability R&D Programme

Smart Cargo Handling Equipment and Charging Station for Port Sustainable Energy Management

Principal Investigator: Assistant Professor Dr. Lam Siu Lee Jasmine,

NTU

Co-Investigator: Dr. Anshuman Tripathi, NTU; Satyajit Athlekar, NTU

Industry collaborator: PSA

July 2015

@ Motivation

Current Generation of Cargo Handling Equipment at Port

Labour intensive

CO2 , SOx emission

Fully electric and fully automated vehicles are not available and they require longer charging time.

Not energy efficient

Not very cost efficient

* Project objectives

a) Conduct a feasibility study of adopting charging station in cargo handling

equipment.

b) Design and model the energy storage system of forklift to achieve port sustainable

energy management and efficient port operations.

c) Design and develop a fully featured battery management system (BMS);

Demonstrate on a forklift as prototype.

c) Develop a charging station system for a real size forklift.

@ Proposed Concept

Supercapacitor technologies which will allow a 24/7 fully electric solution

1. The energy supply is from super capacitors only, with battery back-ups. 2. Cargo operations will be continuous as the super capacitors are being charged at every unloading/ loading station. 3. Super capacitors employment results in fast charging, regeneration and extended operation profile. 4. Using limited battery storage for back up only, increases cost effectiveness, reliability and life span.

@

Targets for research outcomes

Year 1

A feasibility study on various cargo handling equipment (forklift) to

quantify the cost, power consumption and pollution reduction of

adopting a charging station system

Year 2

A design on port cargo handling equipment charging station system

Year 3

A prototype of the charging station system for a real size forklift with

field testing at PSA terminal

@

Ability to connect multiple energy packs seamlessly to the Universal power distribution

and management system UPDMS without the need to configure them.

BMS unit will identify the interconnected packs and display the module parameters such as State of Health (SOH), State of Charge (SOC), and State

of Safety (SOS).

The controls will use a self-commissioning scheme to determine the amount of energy to be drawn from a particular pack based on its current

health for best performance and long life.

Energy Research Institute @ NTU (ERI@N)

1 CleanTech Loop, #06-04 CleanTech One, Singapore

637151

Phone: (65) 6592 1786 / 2468 Fax: (65) 6694 6217 [email protected]

Autonomous Vehicles & Electro-mobility

Overview

* RD&D Focus

Public transport solution

including first/last mile transport

based on Autonomous Vehicles

High energy density, active

balancing

Autonomous Public Buses with

Fleet management

Support the LTA in Technology

Qualification of Autonomous

Vehicles and long term introduce

a Singapore certification scheme

* Mobility on Demand solutions tested @ NTU

Loop 1: Cleantech park

– Hall 11

Loop 2: Nanyang Executive

Center

Loop 3: NTU Admin-

UHC

Three Locations with low connectivity to public transport

* Autonomous Public Bus

- Robotics kit for a Bus

- Validation @ bus depot and in the NTU-Clean Tech Park

Design of robotics kit for conversion

Time-lines

Simulating & testing in a given

environment

* Autonomous Vehicle Centre of Excellence

@ NTU Partners: LTA, BMW, TUM-CREATE

Potential partners: TUV-SUD, MIRA, TNO

Goal:

Support the LTA in Technology Qualification of Autonomous Vehicles and

long term introduce a Singapore certification scheme

Short term: Support the LTA as technical partner in deploying AV pilot

projects

Research Components

Capability Development in Autonomous Vehicles

Sensing & sensors, controls, intelligence

Construction of a “Singapore Traffic Model”

Record analyze traffic in Singapore to create a model of its traffic including

behavior of drivers, motorbike rides and pedestrians

Develop AV testing procedures

Cybersecurity for Autonomous Vehicles

* AV Centre of Excellence @ NTU

• RFI Participants to submit AV performance data to evaluate robustness of test framework

• Operate test circuit

Management, Standards &

Roadmap

Conduct & Manage AV tests

Optimization of Traffic

AV Cyber Security

• Design simulation models for testing

• Design and build test circuit

• Set test benchmarks for all scenarios

• Simulation model to study optimization of traffic network

• Controlled and normal field environment

• Conduct research to analyze and develop mitigation methods for cyber security threats

CoE R&D Programmes^ CoE Test Circuit Operation

Partners: LTA (land transport authority), JTC (Jurong Town Council)

Four Pillars:

* Phases and Key Milestones

Pre-trial Safety Demo before

trial

Small-scale

Test-bed

Environment

Trial w/ driver & full control

En

vir

on

me

nt

Ph

as

e

Controlled

Environment

/Circuit

Operational Trial

w/ driver & full control

Operational Trial

driver w/ limited control or no safety

driver

Complex Environment

Security-by-Design Process and Methodology

1) Threat Risk Assessment (inclusive of security requirements): All security risks of the AV to be identified and assessed

2) Security Design: Approval of Security Design and trade-offs

3) AV Cyber Security Testing: Completion and Acceptance of Testing

Milestone 3

AV

Cy

be

rse

cu

rit

y

Tim

eli

ne

2016 – 2017 Demonstration/Prototype Trial

2018 – 2019 Operational Trial

2020 – 2025 Pilot Deployment

To develop further based on Security-by-Design Process and Methodology

Upon passing the ‘Complex Environment’ stage,

the AV will be allowed to start trial with limited

participants and gradually progress to driver w/

limited control or w/o driver

* NTU Field Test Facility @ Clean Tech

Ahead

Blindspot mirror

EXISTINGSUBSTATION

GARAGE/WORKSHOP

146m

127

BusStop1

BusStop2

Carpark

42

66

26

20

Hump

Ahead

21

Slope

SCourse CrankCourse

Bus

BUS

47

62

• Cross junction traffic light (dual

carriage way; 2 directional)

• T junction traffic light

• 1 x Bus stop at single carriage

• Road Hump

• Car Park Gantry

• Blind spot mirror

• Merging lanes

• Slip road (Pedestrian crossing)

• Long stretch of road

• Junction with no traffic lights

Features:

* Artist Impression of Test Track 59

* 60

Thank You!

autonomous vehicles & electro-mobility

Documents