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S.M.A.A. Kerst
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1
After decades of incremental change in the automotive industry, we now face an era of disruption as environmental concerns and social change propel the introduction of electric vehicles and vehicle automation. Besides the clear benefit of zero-emission transport for society, there is a strong commercial incentive for automated driving, as it will lead to more efficient and safer mobility. A vast amount of research and development is therefore dedicated to its realization.
As human drivers are progressively taken out of the loop, intelligent vehicles impose increasing demands on the highly complex control loop, from measurement and perception to vehicle control. Of particular interest are limit and critical conditions, as optimal performance in these situations is paramount to maximize safety. Therefore, accurate real-time knowledge of the wheel forces is essential, since it represents the tire-road interaction of the individual wheels, determining vehicle behaviour and its handling limits. However, no commercially feasible method is available for the measurement of these important vehicle states.
Current vehicle control systems circumvent this measurement issue by focusing on downstream effects, such as wheel slip and body accelerations. Due to the focus on secondary effects these systems are overly complex and lead to sub-optimal performance. For optimal vehicle control of future intelligent vehicles, therefore, the development of wheel force measurement is considered invaluable. By providing direct access to the most important control variables for dynamics control, such measurement allows for less complex control algorithms with improved performance and robustness, and hence will lead to safer mobility.
Although various approaches for the reconstruction of wheel forces have been developed, no cost effective method is yet available. This can be explained by the fact that load measurement approaches generally require mechanical load decoupling to avoid crosstalk, something that is difficult to achieve on a wheel-end suspension setup that is already complex on itself. In this thesis, a novel method for wheel force reconstruction is proposed via load measurement at bearing level.
iii
The concept of bearing load measurement dates back to the early ’70s and has been investigated by all major bearing manufacturers ever since. This has led to various measurement approaches based on relative ring displacement and outer-ring deformation. Despite all efforts, currently still no accurate nor robust approach for multi-dimensional load reconstruction is available. The state-of-the-art provides unsatisfying results due to the complexity of bearing behaviour and the inability of the currently applied data-driven methods to leverage unique bearing characteristics.
In this thesis a novel approach to bearing load reconstruction is proposed based on outer-ring deformation measurement and real-time simulation of bearing physics. The novel approach includes an explicit description of important physical effects as the rearrangement of rolling elements and the one-dimensional nature of their load transfer. As such it captures the bearing behaviour and allows to make use of its unique characteristics. The proposed approach is based on Kalman filtering and includes two independent physical models: a bearing strain model and a bearing load model.
The bearing strain model defines the outer-ring surface strain variation as a function of the local rolling element loading and location. The proposed model provides a simple though effective continuous and parameterized description of this behaviour. The model is implemented in an Extended Kalman Filter as a means of signal conditioning to estimate local rolling element forces from the measured outer-ring strain. By considering the change of strain due to the reallocation of rolling elements over time, a differential measurement is performed that results in invariance to thermal effects.
The proposed bearing load model is an extension of traditional rigid bearing modelling by a semi-analytical description of outer-ring flexibility. The latter is achieved by static deformation shapes and a Fourier series-based compliance approximation. The proposed model thereby provides a computationally effective but highly accurate description of rolling element forces for common bearing designs, in which significant raceway deformation occurs. Included in an Unscented Kalman Filter, the model provides the relationship between the estimated rolling element forces and the bearing loading and as such serves as a load reconstruction method. By explicit description of the individual one-dimensional element forces the approach considers the internal load decoupling effect and thereby limits crosscoupling on the estimated loads.
The wheel load reconstruction algorithm has been validated in both laboratory and field conditions on a production vehicle wheel-end bearing instrumented with
iv
strain gauges. The study in laboratory conditions was performed on a bearing test setup at our industrial partner whereas the field validation has been performed on a dedicated test vehicle prepared as part of this thesis. Besides the proposed approach, a state-of-the-art algorithm and a variant including the model based signal conditioning method are evaluated to properly assess the results.
The experimental results show that the proposed approach leads to a considerable improvement in accuracy, reproducibility and robustness in comparison to the state-of-the-art data-driven approach. The proposed strain model-based conditioning approach leads to higher reproducibility and improved accuracy of up to 5 percent full scale due to its invariance to thermal effects and ability to discriminate in- and outboard rolling element forces. Additionally, the model-based load reconstruction method further improves accuracy by leveraging the internal bearing load decoupling behaviour to avoid crosstalk. This results in an improvement of over 5 percent full scale for combined loading conditions. Additionally, the approach is more robust, as important relationships are captured by modelling. The latter is well observed for loading conditions outside the calibration domain as an accuracy improvement of 6.8 to 18.4 percent full scale is achieved for the various reconstructed loads. The application of modelling furthermore leads to a significant reduction of parameters subject to calibration and provides physical meaning to these parameters.
Finally, an application study on anti-lock braking was performed to investigate both the load reconstruction performance in dynamic loading conditions and the advantages of load information for vehicle dynamics control. The study shows that sufficient signal bandwidth is provided and confirms the value of direct wheel force measurement for anti-lock braking control. In particular, as traditional difficulties like velocity estimation and slip threshold determination are circumvented whilst the effects of road friction fluctuations and brake efficiency are minimized.
By providing an accurate, robust and scalable solution for the processing of bearing outer-ring strain to the bearing loading, this thesis sets an important step towards a commercially viable solution for wheel-end load measurement. In addition, it is shown how this new information could push the boundaries of vehicle dynamics control. Next is the development of a suitable hardware setup to apply these results in a commercial solution, a topic currently pursued by the author. ...
As human drivers are progressively taken out of the loop, intelligent vehicles impose increasing demands on the highly complex control loop, from measurement and perception to vehicle control. Of particular interest are limit and critical conditions, as optimal performance in these situations is paramount to maximize safety. Therefore, accurate real-time knowledge of the wheel forces is essential, since it represents the tire-road interaction of the individual wheels, determining vehicle behaviour and its handling limits. However, no commercially feasible method is available for the measurement of these important vehicle states.
Current vehicle control systems circumvent this measurement issue by focusing on downstream effects, such as wheel slip and body accelerations. Due to the focus on secondary effects these systems are overly complex and lead to sub-optimal performance. For optimal vehicle control of future intelligent vehicles, therefore, the development of wheel force measurement is considered invaluable. By providing direct access to the most important control variables for dynamics control, such measurement allows for less complex control algorithms with improved performance and robustness, and hence will lead to safer mobility.
Although various approaches for the reconstruction of wheel forces have been developed, no cost effective method is yet available. This can be explained by the fact that load measurement approaches generally require mechanical load decoupling to avoid crosstalk, something that is difficult to achieve on a wheel-end suspension setup that is already complex on itself. In this thesis, a novel method for wheel force reconstruction is proposed via load measurement at bearing level.
iii
The concept of bearing load measurement dates back to the early ’70s and has been investigated by all major bearing manufacturers ever since. This has led to various measurement approaches based on relative ring displacement and outer-ring deformation. Despite all efforts, currently still no accurate nor robust approach for multi-dimensional load reconstruction is available. The state-of-the-art provides unsatisfying results due to the complexity of bearing behaviour and the inability of the currently applied data-driven methods to leverage unique bearing characteristics.
In this thesis a novel approach to bearing load reconstruction is proposed based on outer-ring deformation measurement and real-time simulation of bearing physics. The novel approach includes an explicit description of important physical effects as the rearrangement of rolling elements and the one-dimensional nature of their load transfer. As such it captures the bearing behaviour and allows to make use of its unique characteristics. The proposed approach is based on Kalman filtering and includes two independent physical models: a bearing strain model and a bearing load model.
The bearing strain model defines the outer-ring surface strain variation as a function of the local rolling element loading and location. The proposed model provides a simple though effective continuous and parameterized description of this behaviour. The model is implemented in an Extended Kalman Filter as a means of signal conditioning to estimate local rolling element forces from the measured outer-ring strain. By considering the change of strain due to the reallocation of rolling elements over time, a differential measurement is performed that results in invariance to thermal effects.
The proposed bearing load model is an extension of traditional rigid bearing modelling by a semi-analytical description of outer-ring flexibility. The latter is achieved by static deformation shapes and a Fourier series-based compliance approximation. The proposed model thereby provides a computationally effective but highly accurate description of rolling element forces for common bearing designs, in which significant raceway deformation occurs. Included in an Unscented Kalman Filter, the model provides the relationship between the estimated rolling element forces and the bearing loading and as such serves as a load reconstruction method. By explicit description of the individual one-dimensional element forces the approach considers the internal load decoupling effect and thereby limits crosscoupling on the estimated loads.
The wheel load reconstruction algorithm has been validated in both laboratory and field conditions on a production vehicle wheel-end bearing instrumented with
iv
strain gauges. The study in laboratory conditions was performed on a bearing test setup at our industrial partner whereas the field validation has been performed on a dedicated test vehicle prepared as part of this thesis. Besides the proposed approach, a state-of-the-art algorithm and a variant including the model based signal conditioning method are evaluated to properly assess the results.
The experimental results show that the proposed approach leads to a considerable improvement in accuracy, reproducibility and robustness in comparison to the state-of-the-art data-driven approach. The proposed strain model-based conditioning approach leads to higher reproducibility and improved accuracy of up to 5 percent full scale due to its invariance to thermal effects and ability to discriminate in- and outboard rolling element forces. Additionally, the model-based load reconstruction method further improves accuracy by leveraging the internal bearing load decoupling behaviour to avoid crosstalk. This results in an improvement of over 5 percent full scale for combined loading conditions. Additionally, the approach is more robust, as important relationships are captured by modelling. The latter is well observed for loading conditions outside the calibration domain as an accuracy improvement of 6.8 to 18.4 percent full scale is achieved for the various reconstructed loads. The application of modelling furthermore leads to a significant reduction of parameters subject to calibration and provides physical meaning to these parameters.
Finally, an application study on anti-lock braking was performed to investigate both the load reconstruction performance in dynamic loading conditions and the advantages of load information for vehicle dynamics control. The study shows that sufficient signal bandwidth is provided and confirms the value of direct wheel force measurement for anti-lock braking control. In particular, as traditional difficulties like velocity estimation and slip threshold determination are circumvented whilst the effects of road friction fluctuations and brake efficiency are minimized.
By providing an accurate, robust and scalable solution for the processing of bearing outer-ring strain to the bearing loading, this thesis sets an important step towards a commercially viable solution for wheel-end load measurement. In addition, it is shown how this new information could push the boundaries of vehicle dynamics control. Next is the development of a suitable hardware setup to apply these results in a commercial solution, a topic currently pursued by the author. ...
After decades of incremental change in the automotive industry, we now face an era of disruption as environmental concerns and social change propel the introduction of electric vehicles and vehicle automation. Besides the clear benefit of zero-emission transport for society, there is a strong commercial incentive for automated driving, as it will lead to more efficient and safer mobility. A vast amount of research and development is therefore dedicated to its realization.
As human drivers are progressively taken out of the loop, intelligent vehicles impose increasing demands on the highly complex control loop, from measurement and perception to vehicle control. Of particular interest are limit and critical conditions, as optimal performance in these situations is paramount to maximize safety. Therefore, accurate real-time knowledge of the wheel forces is essential, since it represents the tire-road interaction of the individual wheels, determining vehicle behaviour and its handling limits. However, no commercially feasible method is available for the measurement of these important vehicle states.
Current vehicle control systems circumvent this measurement issue by focusing on downstream effects, such as wheel slip and body accelerations. Due to the focus on secondary effects these systems are overly complex and lead to sub-optimal performance. For optimal vehicle control of future intelligent vehicles, therefore, the development of wheel force measurement is considered invaluable. By providing direct access to the most important control variables for dynamics control, such measurement allows for less complex control algorithms with improved performance and robustness, and hence will lead to safer mobility.
Although various approaches for the reconstruction of wheel forces have been developed, no cost effective method is yet available. This can be explained by the fact that load measurement approaches generally require mechanical load decoupling to avoid crosstalk, something that is difficult to achieve on a wheel-end suspension setup that is already complex on itself. In this thesis, a novel method for wheel force reconstruction is proposed via load measurement at bearing level.
iii
The concept of bearing load measurement dates back to the early ’70s and has been investigated by all major bearing manufacturers ever since. This has led to various measurement approaches based on relative ring displacement and outer-ring deformation. Despite all efforts, currently still no accurate nor robust approach for multi-dimensional load reconstruction is available. The state-of-the-art provides unsatisfying results due to the complexity of bearing behaviour and the inability of the currently applied data-driven methods to leverage unique bearing characteristics.
In this thesis a novel approach to bearing load reconstruction is proposed based on outer-ring deformation measurement and real-time simulation of bearing physics. The novel approach includes an explicit description of important physical effects as the rearrangement of rolling elements and the one-dimensional nature of their load transfer. As such it captures the bearing behaviour and allows to make use of its unique characteristics. The proposed approach is based on Kalman filtering and includes two independent physical models: a bearing strain model and a bearing load model.
The bearing strain model defines the outer-ring surface strain variation as a function of the local rolling element loading and location. The proposed model provides a simple though effective continuous and parameterized description of this behaviour. The model is implemented in an Extended Kalman Filter as a means of signal conditioning to estimate local rolling element forces from the measured outer-ring strain. By considering the change of strain due to the reallocation of rolling elements over time, a differential measurement is performed that results in invariance to thermal effects.
The proposed bearing load model is an extension of traditional rigid bearing modelling by a semi-analytical description of outer-ring flexibility. The latter is achieved by static deformation shapes and a Fourier series-based compliance approximation. The proposed model thereby provides a computationally effective but highly accurate description of rolling element forces for common bearing designs, in which significant raceway deformation occurs. Included in an Unscented Kalman Filter, the model provides the relationship between the estimated rolling element forces and the bearing loading and as such serves as a load reconstruction method. By explicit description of the individual one-dimensional element forces the approach considers the internal load decoupling effect and thereby limits crosscoupling on the estimated loads.
The wheel load reconstruction algorithm has been validated in both laboratory and field conditions on a production vehicle wheel-end bearing instrumented with
iv
strain gauges. The study in laboratory conditions was performed on a bearing test setup at our industrial partner whereas the field validation has been performed on a dedicated test vehicle prepared as part of this thesis. Besides the proposed approach, a state-of-the-art algorithm and a variant including the model based signal conditioning method are evaluated to properly assess the results.
The experimental results show that the proposed approach leads to a considerable improvement in accuracy, reproducibility and robustness in comparison to the state-of-the-art data-driven approach. The proposed strain model-based conditioning approach leads to higher reproducibility and improved accuracy of up to 5 percent full scale due to its invariance to thermal effects and ability to discriminate in- and outboard rolling element forces. Additionally, the model-based load reconstruction method further improves accuracy by leveraging the internal bearing load decoupling behaviour to avoid crosstalk. This results in an improvement of over 5 percent full scale for combined loading conditions. Additionally, the approach is more robust, as important relationships are captured by modelling. The latter is well observed for loading conditions outside the calibration domain as an accuracy improvement of 6.8 to 18.4 percent full scale is achieved for the various reconstructed loads. The application of modelling furthermore leads to a significant reduction of parameters subject to calibration and provides physical meaning to these parameters.
Finally, an application study on anti-lock braking was performed to investigate both the load reconstruction performance in dynamic loading conditions and the advantages of load information for vehicle dynamics control. The study shows that sufficient signal bandwidth is provided and confirms the value of direct wheel force measurement for anti-lock braking control. In particular, as traditional difficulties like velocity estimation and slip threshold determination are circumvented whilst the effects of road friction fluctuations and brake efficiency are minimized.
By providing an accurate, robust and scalable solution for the processing of bearing outer-ring strain to the bearing loading, this thesis sets an important step towards a commercially viable solution for wheel-end load measurement. In addition, it is shown how this new information could push the boundaries of vehicle dynamics control. Next is the development of a suitable hardware setup to apply these results in a commercial solution, a topic currently pursued by the author.
As human drivers are progressively taken out of the loop, intelligent vehicles impose increasing demands on the highly complex control loop, from measurement and perception to vehicle control. Of particular interest are limit and critical conditions, as optimal performance in these situations is paramount to maximize safety. Therefore, accurate real-time knowledge of the wheel forces is essential, since it represents the tire-road interaction of the individual wheels, determining vehicle behaviour and its handling limits. However, no commercially feasible method is available for the measurement of these important vehicle states.
Current vehicle control systems circumvent this measurement issue by focusing on downstream effects, such as wheel slip and body accelerations. Due to the focus on secondary effects these systems are overly complex and lead to sub-optimal performance. For optimal vehicle control of future intelligent vehicles, therefore, the development of wheel force measurement is considered invaluable. By providing direct access to the most important control variables for dynamics control, such measurement allows for less complex control algorithms with improved performance and robustness, and hence will lead to safer mobility.
Although various approaches for the reconstruction of wheel forces have been developed, no cost effective method is yet available. This can be explained by the fact that load measurement approaches generally require mechanical load decoupling to avoid crosstalk, something that is difficult to achieve on a wheel-end suspension setup that is already complex on itself. In this thesis, a novel method for wheel force reconstruction is proposed via load measurement at bearing level.
iii
The concept of bearing load measurement dates back to the early ’70s and has been investigated by all major bearing manufacturers ever since. This has led to various measurement approaches based on relative ring displacement and outer-ring deformation. Despite all efforts, currently still no accurate nor robust approach for multi-dimensional load reconstruction is available. The state-of-the-art provides unsatisfying results due to the complexity of bearing behaviour and the inability of the currently applied data-driven methods to leverage unique bearing characteristics.
In this thesis a novel approach to bearing load reconstruction is proposed based on outer-ring deformation measurement and real-time simulation of bearing physics. The novel approach includes an explicit description of important physical effects as the rearrangement of rolling elements and the one-dimensional nature of their load transfer. As such it captures the bearing behaviour and allows to make use of its unique characteristics. The proposed approach is based on Kalman filtering and includes two independent physical models: a bearing strain model and a bearing load model.
The bearing strain model defines the outer-ring surface strain variation as a function of the local rolling element loading and location. The proposed model provides a simple though effective continuous and parameterized description of this behaviour. The model is implemented in an Extended Kalman Filter as a means of signal conditioning to estimate local rolling element forces from the measured outer-ring strain. By considering the change of strain due to the reallocation of rolling elements over time, a differential measurement is performed that results in invariance to thermal effects.
The proposed bearing load model is an extension of traditional rigid bearing modelling by a semi-analytical description of outer-ring flexibility. The latter is achieved by static deformation shapes and a Fourier series-based compliance approximation. The proposed model thereby provides a computationally effective but highly accurate description of rolling element forces for common bearing designs, in which significant raceway deformation occurs. Included in an Unscented Kalman Filter, the model provides the relationship between the estimated rolling element forces and the bearing loading and as such serves as a load reconstruction method. By explicit description of the individual one-dimensional element forces the approach considers the internal load decoupling effect and thereby limits crosscoupling on the estimated loads.
The wheel load reconstruction algorithm has been validated in both laboratory and field conditions on a production vehicle wheel-end bearing instrumented with
iv
strain gauges. The study in laboratory conditions was performed on a bearing test setup at our industrial partner whereas the field validation has been performed on a dedicated test vehicle prepared as part of this thesis. Besides the proposed approach, a state-of-the-art algorithm and a variant including the model based signal conditioning method are evaluated to properly assess the results.
The experimental results show that the proposed approach leads to a considerable improvement in accuracy, reproducibility and robustness in comparison to the state-of-the-art data-driven approach. The proposed strain model-based conditioning approach leads to higher reproducibility and improved accuracy of up to 5 percent full scale due to its invariance to thermal effects and ability to discriminate in- and outboard rolling element forces. Additionally, the model-based load reconstruction method further improves accuracy by leveraging the internal bearing load decoupling behaviour to avoid crosstalk. This results in an improvement of over 5 percent full scale for combined loading conditions. Additionally, the approach is more robust, as important relationships are captured by modelling. The latter is well observed for loading conditions outside the calibration domain as an accuracy improvement of 6.8 to 18.4 percent full scale is achieved for the various reconstructed loads. The application of modelling furthermore leads to a significant reduction of parameters subject to calibration and provides physical meaning to these parameters.
Finally, an application study on anti-lock braking was performed to investigate both the load reconstruction performance in dynamic loading conditions and the advantages of load information for vehicle dynamics control. The study shows that sufficient signal bandwidth is provided and confirms the value of direct wheel force measurement for anti-lock braking control. In particular, as traditional difficulties like velocity estimation and slip threshold determination are circumvented whilst the effects of road friction fluctuations and brake efficiency are minimized.
By providing an accurate, robust and scalable solution for the processing of bearing outer-ring strain to the bearing loading, this thesis sets an important step towards a commercially viable solution for wheel-end load measurement. In addition, it is shown how this new information could push the boundaries of vehicle dynamics control. Next is the development of a suitable hardware setup to apply these results in a commercial solution, a topic currently pursued by the author.
Bearing load estimation would form a valuable addition to the fields of condition monitoring and system control. Despite effort spend on its development by all major bearing manufacturers no product solution has come to market yet. This can be attributed to both the complexity in conditioning of the strain measurement as well as its non-linearity with respect to the bearing loading. To address these issues, this paper proposes a novel approach based on modeling of the physical behavior of the bearing. An Extended Kalman Filter including a novel strain model is applied for signal conditioning whereas an Unscented Kalman Filter including a semi-analytical bearing model is proposed for reconstruction of the bearing load. An experimental study in both laboratory and field conditions shows that the proposed cascaded Kalman filtering approach leads to accurate estimates for all four considered bearings loads in various loading conditions. Besides an improvement on accuracy, the novel approach leads to a reduction in calibration effort.
...
Bearing load estimation would form a valuable addition to the fields of condition monitoring and system control. Despite effort spend on its development by all major bearing manufacturers no product solution has come to market yet. This can be attributed to both the complexity in conditioning of the strain measurement as well as its non-linearity with respect to the bearing loading. To address these issues, this paper proposes a novel approach based on modeling of the physical behavior of the bearing. An Extended Kalman Filter including a novel strain model is applied for signal conditioning whereas an Unscented Kalman Filter including a semi-analytical bearing model is proposed for reconstruction of the bearing load. An experimental study in both laboratory and field conditions shows that the proposed cascaded Kalman filtering approach leads to accurate estimates for all four considered bearings loads in various loading conditions. Besides an improvement on accuracy, the novel approach leads to a reduction in calibration effort.
This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.
...
This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.
Active vehicle safety and driving assistance systems can be made more efficient, more robust and less complex if wheel load information would be available. Although this information could be determined via numerous different methods, due to various reasons, no commercially feasible approach has yet been introduced. In this paper the approach of bearing load estimation is topic of interest. Using the bearing for load measurement has considerable advantages making it commercially attractive as: i) it can be performed on a non-rotating part, ii) all wheel loads can be measured and iii) usually the bearing serves the entire lifetime of the vehicle. This paper proposes a novel approach for the determination of wheel loading. This new approach, based on the strain variance on the surface of the bearing outer ring, is tested on a dedicated bearing test setup. The experimental results show that the approach allows for the determination of all three force vectors and two moments in different load conditions with sufficient accuracy and bandwidth suitable for the application in vehicle dynamics control.
...
Active vehicle safety and driving assistance systems can be made more efficient, more robust and less complex if wheel load information would be available. Although this information could be determined via numerous different methods, due to various reasons, no commercially feasible approach has yet been introduced. In this paper the approach of bearing load estimation is topic of interest. Using the bearing for load measurement has considerable advantages making it commercially attractive as: i) it can be performed on a non-rotating part, ii) all wheel loads can be measured and iii) usually the bearing serves the entire lifetime of the vehicle. This paper proposes a novel approach for the determination of wheel loading. This new approach, based on the strain variance on the surface of the bearing outer ring, is tested on a dedicated bearing test setup. The experimental results show that the approach allows for the determination of all three force vectors and two moments in different load conditions with sufficient accuracy and bandwidth suitable for the application in vehicle dynamics control.
The measurement and estimation of wheel loads is an interesting and complex topic relevant for vehicle dynamics control. Accurate wheel load information allows for more straight-forward, more robust and more efficient control. In this paper a novel model based wheel load reconstruction approach is presented. An Unscented Kalman Filter is used to reconstruct the unknown wheel loads by analysis of the deformation of the bearing outer-ring. The performance of the approach is demonstrated by field tests using an instrumented passenger car. Results show that the proposed approach is well able to reconstruct both tilting and self-aligning moments as well as lateral and vertical wheel forces during various steering maneuvers.
...
The measurement and estimation of wheel loads is an interesting and complex topic relevant for vehicle dynamics control. Accurate wheel load information allows for more straight-forward, more robust and more efficient control. In this paper a novel model based wheel load reconstruction approach is presented. An Unscented Kalman Filter is used to reconstruct the unknown wheel loads by analysis of the deformation of the bearing outer-ring. The performance of the approach is demonstrated by field tests using an instrumented passenger car. Results show that the proposed approach is well able to reconstruct both tilting and self-aligning moments as well as lateral and vertical wheel forces during various steering maneuvers.
Research objective: Anti-lock braking algorithms use either/both wheel deceleration and wheel slip to obtain a stable limit cycle around the friction peak to guarantee vehicle steerability and to minimize braking distance. However, both control variables pose several well-known issues regarding ABS control. The usage of wheel loads, for instance estimated based on bearing deformation, could provide a solution to these control variable related difficulties. In this paper, a wheel load based method to control wheel slip is presented and implemented in a novel Anti-lock Braking algorithm. Due to the fundamentally different approach to tackle the issue, numerous well known pitfalls of traditional Anti-lock Braking Systems can be avoided.
Methodology: A mathematical derivation of the quarter car model provides the conditions in which wheel load measurement allows for determination of the derivative of wheel slip. Based on this theory, a novel ABS algorithm is proposed. It consists of two operational phases to control the wheel slip derivative and a phase switching mechanism, all based solely on wheel loads. Furthermore a methodology of wheel load estimation based on bearing deformation measurement is proposed. Finally, an experimental on-road investigation of the load estimation and proposed algorithm is carried out using an instrumented test vehicle.
Results: An on-road investigation with a test vehicle demonstrates the accuracy of wheel load estimation based on bearing deformation. The estimated loads are used in a novel ABS algorithm to demonstrate the feasibility and advantages of load based ABS control.
Limitations of this study: Only straight-line braking is considered as the method of load estimation is currently unable to provide the required bandwidth on estimation of loads when steering.
What does the paper offer that is new in the field: Current research in the field of ABS algorithms is primarily focused on wheel slip and/or wheel deceleration control. The presented study investigates a fundamentally different approach by the use of a novel sensor.
Conclusion: Based on a mathematical derivation a novel load-based ABS algorithm is proposed. Furthermore a methodology of load sensing by the use of instrumented bearings is presented. The performance of both load sensing and the Anti-lock braking algorithm has been checked via experimental testing using an instrumented test vehicle.
...
Research objective: Anti-lock braking algorithms use either/both wheel deceleration and wheel slip to obtain a stable limit cycle around the friction peak to guarantee vehicle steerability and to minimize braking distance. However, both control variables pose several well-known issues regarding ABS control. The usage of wheel loads, for instance estimated based on bearing deformation, could provide a solution to these control variable related difficulties. In this paper, a wheel load based method to control wheel slip is presented and implemented in a novel Anti-lock Braking algorithm. Due to the fundamentally different approach to tackle the issue, numerous well known pitfalls of traditional Anti-lock Braking Systems can be avoided.
Methodology: A mathematical derivation of the quarter car model provides the conditions in which wheel load measurement allows for determination of the derivative of wheel slip. Based on this theory, a novel ABS algorithm is proposed. It consists of two operational phases to control the wheel slip derivative and a phase switching mechanism, all based solely on wheel loads. Furthermore a methodology of wheel load estimation based on bearing deformation measurement is proposed. Finally, an experimental on-road investigation of the load estimation and proposed algorithm is carried out using an instrumented test vehicle.
Results: An on-road investigation with a test vehicle demonstrates the accuracy of wheel load estimation based on bearing deformation. The estimated loads are used in a novel ABS algorithm to demonstrate the feasibility and advantages of load based ABS control.
Limitations of this study: Only straight-line braking is considered as the method of load estimation is currently unable to provide the required bandwidth on estimation of loads when steering.
What does the paper offer that is new in the field: Current research in the field of ABS algorithms is primarily focused on wheel slip and/or wheel deceleration control. The presented study investigates a fundamentally different approach by the use of a novel sensor.
Conclusion: Based on a mathematical derivation a novel load-based ABS algorithm is proposed. Furthermore a methodology of load sensing by the use of instrumented bearings is presented. The performance of both load sensing and the Anti-lock braking algorithm has been checked via experimental testing using an instrumented test vehicle.