HEV TCP Task 26 Workshop 9: Wireless Charging for EVs 

(6-7 Nov. 2018 in Detroit, Michigan USA)

“NREL’s Managed WPT Experiences and Lessons Learned”

Presenter

Ahmed Mohamed

Transportation and Hydrogen Systems Center, NREL.
NREL | 2

Introduction/NREL’s Vision for Demonstrating WPT for EV

Description of 25 kW WPT system at NREL’s Shuttle

EMF Testing of On-Vehicle WPT System

Monitoring and Control of the Wireless Charging 

Description of WPTsim Tool for WPT design

Design of Greenville AMD Project using WPTsim

Conclusions/Opportunities
NREL | 

3

Dynamic WPT

Quasi-dynamic WPT

Stationary WPT

vehicle pad

ground pad

PPM

https://www.nbcnews.com/mach/mach/futuristic-roads-may-make-recharging-electric-

cars-thing-past-ncna766456
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 Wirelessly Charged Electric Shuttle

 Momentum Dynamics WPT system

3φ AC

supply Filter EV

battery 

Primary controller Secondary controller

 

Radio 

munications

 

vehicle pad

ground pad

PPM

o Full electric on-demand service

o 16 passenger

o 62.1 kWh battery capacity

o 100 miles range

o 7600 curb weight, including VA

o 6.6 kW on-board conductive charger

o 35.5”x35.5”x2.25” (900x900x57 mm) 

symmetrical square pads

o 25 kW maximum power transfer

o 20 (19-21) kHz nominal operating 

frequency.

o Automatic alignment capability.

o 5”-9.5” (125-240 mm) airgap
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https://www.narda-sts.com/en/

http://www.eenewsautomotive.com/news/one-testsystem-analysing-electromagnetic-fields-5-hz-60-ghz

 Test Methodology

1. Define coordinates.

2. Define a marked safety perimeter.

3. Identify the worst misalignment condition (X, Y, Z, 

pitch, roll and yaw).

4. Define test zones and points

Region I: Under the vehicle

Region II: Around and above the vehicle

Region III: Inside the vehicle

5. Define the standard limits for each zone (2010 

ICNIRP)

Coupler Offset & Gap Max Magnetic Field Max Electric Field

dX dY dZ Location B (μT) Location E (V/m)

+max +max max

+max -max max

-max +max max

-max -max max

“J2954A (WIP) Wireless Power Transfer for Light-Duty Plug-In/ Electric Vehicles and 

Alignment Methodology - SAE International.” 

EHP-50D,

Narda
NREL | 7

X-axis

Y-axis

VA

X-axis

Y-axis

VA

X-axis

Y-axis

VA

X-axis

Y-axis

VA

X-axis

Y-axis

VA

(a) (b) (c)

(d) (e)

EMFs around the vehicle (zone II)

EMFs before/during alignment (Low Power Excitation)

Y-axis

X-axis

GA

× 

× 

× 

× 

× 

× 

× 

× 

× × × × × × 

Z

test region

9"

9"

240" shuttle

20" 20"

8.5"

driver’s 

seat

36"

36"

76"

Y-axis

X-axis VA &GA

front

back

test region

Z × P1

6'

6'

6'

6'

Misalignment Max Brms (μT) Max Erms (V/m)

Position I 16.661 1.7414 

Position II 18.380 2.4091

Position III 17.696 2.5345 

Position IV 17.152 1.7147 

Position V 18.526 2.0853 
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× × × × × 

× 

× 

× 

× 

× 

× 

× bus 

inside

seat

VA

bus outside Y’-axis

X’-axis

A

B

C

EMFs inside the vehicle (zone III)

Test Point Max Brms (μT) Max Erms (V/m)

PA 0.0328 0.0633 

PB 0.0068 0.0380 

PC 1.0362 0.0257 

Magnetic field along X’-axis at a height of 27.25” from the floor of the bus

Magnetic field along Y’-axis at a height of 6.25” from the floor of the bus

Driver seat test points Over VA test points
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NREL Intelligent Campus Integrates: 

o RESs

o ESSs

o Building loads

o EVSEs

- AC level 2

- DC FC (50 kW)

- Wireless Charger (25 kW)

- Bidirectional EV
NREL | 11

 Objective: ‘smart’ integration of wireless charger with surrounding 

infrastructure on NREL campus (e.g. Renewable Generation, Loads, 

other EVSEs, etc. )

Momentum Dynamics 

Grafana System

vehicle pad

ground pad

PPM

Charge Control

SOC

Vehicle status

NREL’s 

campus 

load

Charge 

decision

SOC

Vehicle status

Power transfer

NREL’s Campus Load

Block diagram for the data-flow of the wireless charging control
NREL | 12

Cloudy day results: lack of PV generation

0 5 10 15 20

3500

4000

4500

P L (kW)

load

limit

0 5 10 15 20

-500

0

500

P L (kW)

load

limit

0 5 10 15 20

0

5

Align

0 5 10 15 20

0

50

100

SOC (%)

SOC

Max SOC

Min SOC

0 5 10 15 20

Time (hr)

0

1

2

signal

0 5 10 15 20

2000

4000

P L (kW)

load

limit

0 5 10 15 20

0

1000

2000

3000

P L (kW)

load

limit

0 5 10 15 20

0

5

Align

0 5 10 15 20

0

50

100

SOC (%)

SOC

Max SOC

Min SOC

0 5 10 15 20

Time (hr)

0

1

2

signal

Nice day results: lots of PV generation
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 It is a design optimization tool that 

incorporates driving data, vehicle data 

with charging infrastructure parameters 

(conductive or wireless).

Speed

Position

grade

Driving data

Vehicle’s data

Battery

Motor

Dimensions

etc.

0 0.5 1 1.5 2 2.5

0

10

20

30

Speed (mph)

Type 1

WPT location 1

WPT location 2

WPT location 3

WPT location 4

WPT location 5

WPT location 6

Type 4

Type 4

0 0.5 1 1.5 2 2.5

Time (hr)

-200

-100

0

100

200

Battery power (kW)

65

70

75

SOC (%)

Charger’s data

Power

Efficiency

Conductive

 

Wireless

Power

Efficiency

Positions

Length

WPTsim

Evaluate Fitness

- Charge sustaining

- Min. Battery capacity

- Min. charging infrastructure cost

Generate variables

- Battery capacity

- Track positions

- Track length

- Rated power

 It is capable of providing optimum 

design of wireless infrastructures 

(stationary, dynamic and quasidynamic) for certain road scenario.

 It is utilized to provide designs for 

multiple scenarios such as:

 NREL’s circulator shuttle.

 Greenville AMD Project

Optimization Search Algorithm
NREL | 15

WPTsim

Lt Lr

Wr Wt

Pn

Pn

Wr

S

d

d

Travel direction

Lane direction

T1 R T2

16 passenger, curb weight 

3500 kg, 36 kWh battery 

capacity and about 45 

mph maximum speed

GRT 

AES

Phase 0

Phase 1

0 1 2 3 4 5 6

0

50

0 1 2 3 4 5 6

0

50

Speed (mph)

0 1 2 3 4 5 6

0

50

0 1 2 3 4 5 6

Time (hr)

0

50

-82.35 -82.345 -82.34 -82.335 -82.33 -82.325 -82.32 -82.315 -82.31

Longitude

34.818

34.82

34.822

34.824

34.826

34.828

34.83

34.832

34.834

34.836

34.838

latitude

AET11

AET12

AET13

AET14

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

0

20

40

Speed (mph)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

Time (hr)

-100

0

100

Battery power (kW)

60

80

100

SOC (%)

GRT, AET11 with 17 WPT 

positions (60 kW and 155 m 

track at each position).

1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2

0

10

20

30

40

50

Speed (mph)

1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2

Time (hr)

0

Battery power (kW)

80

SOC (%)
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Parameter Optimal value

# wireless chargers 11 out of 17

Positions [3 4 5 7 8 9 11 13 14 15 17]

Power 80 kW

Battery capacity 12 kWh

# segments per Track 25 (125-meter track length)

Optimal driving performance

Optimal WPT positions

Optimal key design parameters

-82.35 -82.345 -82.34 -82.335 -82.33 -82.325 -82.32 -82.315 -82.31

Longitude

34.815

34.82

34.825

34.83

34.835

34.84

Latitiude

Map of travel with highlighted WPT segments

Full Drivecycle

Segment 1 boundary

Segment 2 boundary

Segment 3 boundary

Segment 4 boundary

Segment 5 boundary

Segment 6 boundary

Segment 7 boundary

Segment 8 boundary

Segment 9 boundary

Segment 10 boundary

Segment 11 boundary

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

0

20

40

Speed (mph)

Type 1

WPT location 1

WPT location 2

WPT location 3

WPT location 4

WPT location 5

WPT location 6

WPT location 7

WPT location 8

WPT location 9

WPT location 10

WPT location 11

Type 4

Type 4

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

Time (hr)

-100

0

100

Battery power (kW)

50

60

70

80

90

SOC (%)

– Optimization Variables:

– Position of each wireless charger.

– Wireless charger power.

– EV’s battery capacity.

– Number of track segments (track length).

– Optimization Objectives:

– Minimum battery capacity.

– Minimum charging infrastructure cost.

– Achieve charge sustaining operation.
NREL | 17

 Extra effort is required for demonstrating the WPT technology in real world 

scenarios starting with closed campus scenarios.

 Collecting data from real-world projects, including NREL’s shuttle one, to be 

utilized for better understanding the technology, control design and validating 

design tools.

 Updating and utilizing WPTsim tool for analyzing more complex charge design 

scenarios (e.g. interstate, urban and rural roads).

 Working to have an EasyMile autonomous shuttle operating at NREL campus with 

the possibility to install a wireless charger to it. 
www.nrel.gov

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy,

LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by U.S.

Department of Energy Office of Energy Efficiency and Renewable Energy Vehicles Technologies Office. The views

expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S.

Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S.

Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published

form of this work, or allow others to do so, for U.S. Government purposes.

NREL/PR-5400-72805