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APPLICATION INFORMATIONGUIDELINES FOR MAPPING SPEED SENSOR TARGETS
By Syed Bilal Ali and Sarkis Dono
Allegro MicroSystems

INTRODUCTION
Speed sensor targets have various application-specific forms,
such as ring magnets with different magnetic properties,
diameters, and numbers of pole pairs, and ferrous gears withdifferent sizes and features. For each target, it is important todetermine if they are compatible with the speed sensor thatwill be used and the air gap range over which the sensor willoperate. This requires finding and analyzing the magnetic
input signal over several placements of the sensor relative tothe target—for example, over rotation of the target and overair gap. The set of magnetic input signal values over target
rotation and sensor position is known as a target map, andthe method to measure, simulate, or calculate these signals isknown as target mapping. This application note describes thevarious techniques that can be used to map customer targets
for speed sensors.

MAPPING SPEED SENSOR TARGETS
USING MAGNETIC SIMULATIONS
If a 3D model or a technical drawing of the target is available,
Allegro can perform magnetic simulations to map the target.
These simulations are performed in Ansys Maxwell or in MATLAB
by creating a sensor and target system, defining movement
parameters, and solving them to find the magnetic fields atthe sensing elements of the sensor.
To perform these simulations, Allegro requires the following
information from customers:• A 3D model of the target, usually available as a STEP file. Forless complex ferrous targets or ring magnets, a technicaldrawing with target dimensions may be sufficient.
• Allegro speed sensor under consideration for the application.
• Any special placement requirements for example any
twist or tilt in the sensor placement.
• Material properties of the target, for example, the typeof ferrous material and the permeability (Ur) for ferrous
targets, or the magnetic material, remanence flux density,(Br), and temperature coefficients for ring magnets.
• Dimensions and motion of any nearby ferrous ormagnetic materials that may influence the magnetic field.
Magnetic simulations can be characterized into two types: ringmagnets with Allegro front-biased sensors and ferrous targets
with Allegro back-biased sensors.

Ring Magnets with Allegro Front-Biased Sensors
Figure 1 shows the steps required to determine the maximum
air gap on a ring magnet model. The ring magnet in the figure
is created from information provided by the customer. A simulation is run for rotation over one pole pair (or one TCYCLE) andover several air gaps, and the peak-to-peak of the differential
magnetic signal is plotted versus air gap. The air gap at which
the peak-to-peak crosses the datasheet-specified minimum
peak-to-peak differential signal value (30 G in Figure 1) is themaximum operating air gap of the sensor.

Figure 1: Ring magnet mapping through simulations

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Similarly, several operating characteristics and limits described inthe datasheets of Allegro front-biased sensors can be calculated
from the input magnetic fields. These include:•••••

Operating differential magnetic input
Operating single-ended field magnitude
Signal cycle-cycle variationSwitch point separation
Phase shift

These operating characteristics depend on the Allegro sensor
under consideration, and it is important to determine if thespecifications for these operating characteristics will be met toensure the correct operation of the sensor in the application.

Ferrous Targets with Allegro Back-Biased Sensors
For back-biased speed sensors, Allegro datasheets define
specifications such as the maximum air gap on a standard Allegro
ferrous target. Therefore, a customer target mapping must becompared to a mapping of the Allegro target. Figure 2 shows
the procedure to find the maximum air gap on a customer target
through simulations. Both the customer target and the Allegro
standard target are imported into the simulation environment, thematerial properties are defined, and a simulation is performed
over one tooth valley period and over air gap. The maximum air
gap on the customer target is determined by finding the air gap
where the peak-to-peak of the differential magnetic signal on thecustomer target is equal to the peak-to-peak of the differential
magnetic signal on the Allegro target at the datasheet-defined

maximum air gap. For example, in Figure 2, the maximum airgap is determined to be 2 mm on the customer target.
Several operating characteristics and limits described in thedatasheets of Allegro front-biased sensors can be calculated
from the simulated input magnetic fields. These include:
••
•
•
•

Switch point separation
Cycle-to-cycle variation
Signature amplification ratio for targets with signature regions
Dynamic and sudden air gap range
Phase shift

These operating characteristics depend on the Allegro sensorunder consideration, and it is important to determine if thespecifications for these operating characteristics will be met toensure the correct operation of the sensor in the application.

MAPPING SPEED SENSOR TARGETS ON
THE TEST BENCH
If physical targets are available, Allegro labs can perform measurements to map the target on the test bench. Mapping a physicaltarget has the advantage that it considers any small variations
that might be present on the actual target that may be missedby the ideal environment in simulations. Additionally, the fields
measured from a test bench mapping more closely represent
the actual fields the sensor will sense in the application.
Like magnetic simulations, test bench mappings can be characterized into two types.

Figure 2: Ferrous target mapping through simulations

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Mapping Ring Magnets with Allegro FrontBiased Sensors
Figure 3 shows the bench setup for a ring magnet mappingmeasurement. Ring magnets can be mapped using an Allegrolinear sensor to measure the magnetic fields. The setup requires
a rotational stage to rotate the ring magnet at precise angles
and a 3D linear stage set to control the placement of the linear
sensor so that it passes through all air gaps and all sensing
element placements in the speed sensor. The linear sensor

must be placed so that it measures the magnetic field in thedirection that the speed sensor will sense (since Hall parts andGMR parts sense fields in different directions). The magnetic
field over rotation, air gap, and sensing element placements
can be acquired using a data acquisition device or read digitallydepending on the linear sensor being used. Once the fields arefound, differential signals can be calculated, and the maximum
air gap can be determined from the peak-to-peak differential
signal as described in the magnetic simulations section.

Figure 3: Ring magnet mapping bench setup

Mapping Ferrous Targets with Allegro BackBiased Sensors
The method for mapping a ferrous target is different from that ofring magnets such that normally a linear sensor is not required.
Ferrous targets may be mapped using the actual back-biased
Allegro speed sensor that will be used in the application. Themagnetic differential signals can be read out as an analog signal on the pins of the IC or digitally in LSBs. The physical setup(shown in Figure 4) is the same as described for ring magnet
mappings. However, to find the maximum air gap on a customer
ferrous target, an Allegro standard target must be mapped at

the datasheet-defined maximum air gap to find the peak-to-peakdifferential magnetic signals. The customer target can then be
mapped over rotation and over air gap, and maximum air gap
can be determined by finding the air gap at which the peak-topeak differential signal on the customer target is equal to thepeak-to-peak differential signal value on the Allegro target atthe datasheet-defined maximum air gap.
For a physical mapping, in most cases, it may be sufficient tomap just one pole-pair or one tooth valley period. However, it
is recommended to map the full 360° rotation of the target—atleast at one nominal air gap—to ensure that there are no defects
in the target creating undesired magnetic signal shapes.

Figure 4: Ferrous target mapping bench setups

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APPLICATION INFORMATIONCONCLUSION
Mapping techniques may be used to evaluate customer targets
for speed sensor applications. Depending on the informationthat is available, Allegro has the possibility to both simulate andmeasure the magnetic signals sensed by the speed sensors.
These magnetic signals can then be analyzed to determine
the compatibility of the speed sensor to the customer target.

955 PERIMETER ROAD • MANCHESTER, NH 03103 • USA+1-603-626-2300 • FAX: +1-603-641-5336 • ALLEGROMICRO.COM4

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Revision History
NumberDate

Description–May 8, 2023

Initial release

Copyright 2023, Allegro MicroSystems.

The information contained in this document does not constitute any representation, warranty, assurance, guaranty, or inducement by Allegro to the customer with respect to the subject matter of this document. The information being provided does notguarantee that a process based on this information will be reliable, or that Allegro has explored all of the possible failure modes.
It is the customer’s responsibility to do sufficient qualification testing of the final product to ensure that it is reliable and meetsall design requirements.
Copies of this document are considered uncontrolled documents.

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