Novel Dynamic Technique Reducing the Offset
Voltage in a New Hall Effect Sensor
Vlassis N. Petoussis
University of Thessaly. Department of Electrical & Computer Engineering.
The Main Goals
We present a model and numerical analysis of a new Hall effect sensor which
using a novel offset reduction method.
We calculate the function which governs the changes in the electric field inside
the new Hall effect sensor in presence of magnetic field.
Control in MatLab environment the equipotential lines and monitor the
changes when biasing conditions are change.
The combination of his pioneering form and the elaborate sequence of using
the dynamic spinning current technique.
Spinning Current vs Offset Voltage
The offset of the Hall plate is the voltage that
is measured when no magnetic field is applied.
The following equation represents the
theoretical situation, when an offset is added :
V = ISB + V
Figure. 1. An eight contact spinning-current Hall plate with
the possible bias current directions
To reduce the offset, which is time variant,
spinning current Hall plates was developed
For our theoretical approach -- in the
development of the new Hall effect sensor in
this present work, we use for a model (cell like
device) the split-current model. We estimate
the magnetic field resolution and the
appropriate boundary conditions to explain the
electric field and potential inside the sensor
Fig.2 Figure 2: The split-current Hall effect device.
In our split-current model we use Dirichlet (D) and Neumann (N) boundary conditions as we
can see in Fig. 3a. We use Dirichlet boundary conditions in contacts with positive or zero
potential and Neumann boundary conditions elsewhere, especially in regions which the sensor
communicates with the natural environment. With this way the current density in x direction
we need to be a zero, and in y direction to be a non zero.
Figure. 3. The boundary conditions for a split-current element Hall effect device. a) Graphic representation of a simple model in
even phase, with D and N presented the boundary conditions. Dirichlet boundary conditions in contacts with positive or zero potential and
Neumann boundary conditions elsewhere. b) The area of the received Hall voltage tacked in four places of the sensor. We can see that the
margins of the field in our model is well separated each other (black trapezoid areas).
For an p-type and n-type semiconductor we can write respectively:
∂Φ µpB ∂Φ µn B
= −c ( B ) = c( B)
∂x 1 + ( µ p B) 2 ∂x 1 + ( µ n B) 2
These equations give us the dependence of the electric field inside the sensor in presence of
magnetic field. Furthermore these relations allow us to simulate the changes of the equipotential
lines in MatLab environment solving this PDE equations for different values of magnetic
One of the most important problems in our analysis and simulations was the determination of
the drift mobilities. To solve this problem we decide to use the following empirical expressions
µn = (65.0 + 16 −3 0.72
1 + [ NT /(8.5x10 cm )] Vs
447.3 cm 2
µ p = (46.7 + )
1 + [ N T /(6.3x1016 cm −3 )]0.72 Vs
The New Hall Effect Sensor Device
Wheel Hall Sensor (WHS)
In University of Thessaly we designed and we are ready to develop a novel Hall sensor device
which uses elaborate spinning current technique . The novel Hall device that we call
“Wheel Hall Senor (WHS)” is presented in Figures 4a and 4b. The current enters the device,
as presented in the aforementioned Figures, in two phases namely the even phase (PHASE-P)
and the odd phase (PHASE-N).
Figure. 4. The novel Hall device that we call “Wheel Hall Senor” or WHS. (a) The even phase (PHASE-P) (b) the odd phase
The offset reduction method
To reduce the offset, the new Hall effect sensor uses spinning-current technique in the
symmetrical Hall plate. In the offset reduction sequence the direction of the bias current is splited
right and left and the corresponding output voltage is measured on the contacts in 450 to the current
direction in each phase. When sixteen outside and sixteen inside contacts are used, the bias current
is switched 450 for each measurement, the voltage contacts are switched outside to inside
respectively (Fig. 5).
For each phase of the bias current, four output (VH+ and VH-) and input (VH- and VH+) voltages are
measured in a rotating clock wise. Finally for each turn in PHASE-P and PHASE-N, totally sixteen
Hall voltages are measured. Each harmonic biasing current in each phase produces an offset
voltage witch totally in turns gives us the offset cancellation. So offset caused from current IAD in
phase P cancel the offset caused from current ICD in phase N and IAD in phase N cancel the offset
caused from current IAF in phase P. Finally the one offset in one phase cancel the other in next
Figure. 5. The even phases (a) and the odd phases (b). With I we denote the current bias in 450 direction in each measurement
and VH+ and VH- denoted the two Hall Voltage references in each phase (for n-type material).
Field Simulations in MatLab
To complete our analysis we present simulations of the device structure in to control our
theoretical approach that we already developed. The theory to control the electric field of the
device when it is exposed in perpendicular external magnetic field.
In a Matlab environment we solved the Laplace equation inside the device and calculate and
simulate the electric field and the equpotential lines inclination in the WHS in a presence of
magnetic induction, the results represented in figures 6a and 6b.
Fig. 6. The novel Hall device that we call “Wheel Hall Senor” or WHS. (a) The electric field and the equpotential lines in the even
phase (PHASE-P) for B non zero, (b) The electric field and the equpotential lines in the odd phase PHASE-N) for B non zero.
(PHASE- PHASE- zero.
In this presentation we define the method and some of our theoretical simulations in MatLab
environment for a new Hall effect sensor which is uses a novel tehqnique to reduce the offset
voltage. We already to develop this novel Hall sensor (Wheel Hall Sensor) in CADANCE
simulators to take Hall voltage measurements in a semi real conditions. After this we already to
publish the results in future papers.
I would like to thank Pr. Dr. Manolis Vavalis for the useful advices and helpful discussions.
Furthermore I would like to thank the Electrical Engineering & Computer Engineering Department
of the University of Thessaly for the technical support and fulfillment of this project.
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