Development of a Magnetoelastic Torque Sensor for Formula 1 and CHAMP Car Racing Applications

Bitar, S.; Probst, John S.; Garshelis, Ivan J.

doi:10.4271/2000-01-0085

Cited by 10 publications

(4 citation statements)

References 8 publications

(8 reference statements)

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“…The Joule effect and Villari effect can be utilized for actuator and sensor applications, respectively. Magnetostrictive (active) materials have been used in composite structures having other structural non-magnetic (passive) materials in various macro-and micro-scale applications such as gyro sensor (Yoo et al, 2005), strain sensors (Wun-Fogle et al, 1987;Datta and Flatau, 2005), torque sensors (Bitar et al, 2000;Parsons et al, 2008), bioMEMS sensor (Guntupalli et al, 2007), MEMS actuator (Basantkumar et al, 2006), and MEMS sensor (Frommberger et al, 2005). Such applications motivate the development of a modeling framework with the capability of including the non-linear stress and magnetic field dependency of magnetoelastic processes in a structural model, which can account for non-linear structural couplings in a composite structure.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Magnetomechanical Actuators in Laminated Structures

Datta

Atulasimha

Mudivarthi

et al. 2009

Journal of Intelligent Material Systems and Structures

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A magnetomechanical plate model (MMPM) has been developed to predict the elastic and magnetostrictive strains and mechanical stress in laminated structures with magnetostrictive and non-magnetic layers under the simultaneous effect of quasi-static mechanical stress and magnetic field. This model was obtained by combining an energy-based statistical magnetomechanical model with the classical laminated plate theory. The magnetomechanical plate model was used to study a unimorph structure having a magnetostrictive iron—gallium (Galfenol) patch attached to different non-magnetic substrates. The actuation response from the patch was obtained for in-plane axial magnetic field acting on the unimorph. The MMPM was used to predict the normalized tip displacement due to induced-strain actuation in a unimorph cantilever beam and the results were compared with existing modeling techniques. The model was used to study the effect of tensile and compressive axial pre-loads on the actuation response of the structure. A study was also performed to understand the effect of total thickness of the structure, the ratio of the active/ passive layer thickness and the effect of the mechanical properties of different substrate materials on the actuator performance. A non-dimensional parameter ST i (percentage strain transfer) was introduced to explain the behavior of the actuator in extension and bending dominated regimes and a critical thickness ratio (trc) was defined to demarcate these two regimes. The results demonstrate that the model captures the non-linearity in the magnetomechanical process and the different structural couplings.

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Section: Introductionmentioning

confidence: 99%

Modeling of Magnetomechanical Actuators in Laminated Structures

Datta

Atulasimha

Mudivarthi

et al. 2009

Journal of Intelligent Material Systems and Structures

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“…2) Non-Torsion-Shaft Magnetoelastic Detection: In one sensor, ac-excitation is used to detect changes in shaft permeability [77]. In the other type, permanently magnetized shafts or sleeves self-generate a dc-magnetic flux signal [78], [79]. Both sensors operate without contacting the rotating shaft.…”

Section: Engine/transmission/steering Torque Sensorsmentioning

confidence: 99%

Overview of automotive sensors

2001

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An up-to-date review paper on automotive sensors is presented. Attention is focused on sensors used in production automotive systems. The primary sensor technologies in use today are reviewed and are classified according to their three major areas ofautomotive systems application-powertrain, chassis, and body. This subject is extensive. As described in this paper, for use in automotive systems, there are six types of rotational motion sensors, four types of pressure sensors, five types of position sensors, and three types of temperature sensors. Additionally, two types of mass air flow sensors, five types of exhaust gas oxygen sensors, one type of engine knock sensor, four types of linear acceleration sensors, four types of angular-rate sensors, four types of occupant comfort/convenience sensors, two types of near-distance obstacle detection sensors, four types of far-distance obstacle detection sensors, and and ten types of emerging, state-of the-art, sensors technologies are identified.

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“…Measuring the torque in mechanical shafts made of steel is a common challenge found in various industrial applications. Some examples of these applications include marine propulsion systems [ 1 , 2 ], turbine generators [ 3 , 4 , 5 ], robotics [ 6 , 7 , 8 , 9 , 10 ], and automotive [ 11 , 12 , 13 , 14 ] and electromobility applications [ 15 , 16 , 17 ]. Due to the rotation of a mechanical shaft under normal working conditions, powering a typical strain-gauge based torque sensor while collecting data is very challenging [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

A FEM-Based Optimization Method for Driving Frequency of Contactless Magnetoelastic Torque Sensors in Steel Shafts

et al. 2021

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This paper presents a novel finite element method (FEM) of optimization for driving frequency in magneto-mechanical systems using contactless magnetoelastic torque sensors. The optimization technique is based on the generalization of the axial and shear stress dependence of the magnetic permeability tensor. This generalization creates a new possibility for the determination of the torque dependence of a permeability tensor based on measurements of the axial stress on the magnetization curve. Such a possibility of quantitative description of torque dependence of a magnetic permeability tensor has never before been presented. Results from the FEM-based modeling method were validated against a real magnetoelastic torque sensor. The sensitivity characteristics of the model and the real sensor show a maximum using a driving current of similar frequency. Consequently, the proposed method demonstrates the novel possibility of optimizing magnetoelastic sensors for automotive and industrial applications.

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Development of a Magnetoelastic Torque Sensor for Formula 1 and CHAMP Car Racing Applications

Cited by 10 publications

References 8 publications

Modeling of Magnetomechanical Actuators in Laminated Structures

Modeling of Magnetomechanical Actuators in Laminated Structures

Overview of automotive sensors

A FEM-Based Optimization Method for Driving Frequency of Contactless Magnetoelastic Torque Sensors in Steel Shafts

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