EP4701876A1

EP4701876A1 - Model-based tyre explosion detection

Info

Publication number: EP4701876A1
Application number: EP23721404.4A
Authority: EP
Inventors: Jan-Inge Svensson; Dandan Ge; Mats Jonasson
Original assignee: Volvo Truck Corp
Current assignee: Volvo Truck Corp
Priority date: 2023-04-24
Filing date: 2023-04-24
Publication date: 2026-03-04
Also published as: WO2024223019A1

Abstract

A computer system (130, 800) for detecting tyre explosion in a heavy-duty vehicle (100), the computer system (130, 800) comprising processing circuitry configured to: obtain control input data indicative of a control input (475) to one or more motion support devices, MSD, (430) of the heavy-duty vehicle (100), obtain a model (300) of vehicle dynamics configured to predict a motion response by the heavy- duty vehicle (100) to a control input, predict a motion response by the heavy-duty vehicle (100) to the control input (475) using the model (300) of vehicle dynamics, obtain vehicle motion data (445) from a sensor system (440) of the heavy-duty vehicle (100) indicative of an actual motion response by the heavy-duty vehicle (100) to the control input (475), and detect tyre explosion in case a difference between the predicted motion response by the heavy- duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) does not satisfy a first predetermined acceptance criterion.

Description

Docket No.: P2022-1569 / P456436PC00 MODEL-BASED TYRE EXPLOSION DETECTION TECHNICAL FIELD This disclosure relates generally to monitoring and control of heavy-duty vehicles such as trucks, busses, and construction equipment. In particular aspects, the disclosure relates to different forms of computer-implemented tyre explosion detector functions arranged to automatically detect when tyre explosion occurs, such that one or more automated mitigating actions by the vehicle can be triggered. Although the disclosure may be described with respect to a particular vehicle, the disclosure is not restricted to any particular vehicle. BACKGROUND Tyre explosion is an event where a tyre abruptly ruptures, e.g., due to wear or impact. Tyre explosions may lead to vehicle instability and may cause hazard to both the occupants in the vehicle as well as other nearby road users. It is desired to quickly detect when a tyre explosion occurs, such that one or more hazard-mitigating actions can be taken. Tyre pressure monitoring systems (TPMS) are systems arranged to monitor tyre pressure in one or more tyres, often using battery powered tyre pressure sensors arranged inside the tyre and wirelessly connected to a receiver outside the tyre that communicates with a vehicle control system. The TPMS system will trigger generation of a warning signal in case the tyre pressure deviates from a predetermined range of acceptable pressure values. TPMS systems are often capable of detecting tyre explosions successfully. However, some TPMS systems are associated with an unacceptable detection latency, and other TPMS systems have been known to fail in the detection of tyre explosion events, e.g., because the sensor hardware becomes damaged by the forces it is subject to during a tyre explosion. An improved tyre explosion detection system is desired, in particular one that is both robust and of low detection latency. SUMMARY Techniques for automatic detection of tyre explosions are disclosed herein. The techniques may be described in terms of a computer system and/or as methods performed by the computer Docket No.: P2022-1569 / P456436PC00 system. In particular, computer systems are disclosed herein for detecting tyre explosions in a heavy-duty vehicle. The computer system comprises processing circuitry configured to obtain control input data indicative of a control input to one or more motion support devices (MSD) of the heavy-duty vehicle. The processing circuitry is also configured to obtain a model of vehicle dynamics which is set up to predict a motion response by the heavy-duty vehicle to a control input. This allows the processing circuitry to predict a motion response by the heavy- duty vehicle to the control input by using the model of vehicle dynamics. The processing circuitry is also configured to obtain vehicle motion data from a sensor system of the heavy- duty vehicle indicative of an actual motion response by the heavy-duty vehicle to the control input, and detect tyre explosion in case a difference between the predicted motion response by the heavy-duty vehicle and the actual motion response by the heavy-duty vehicle does not satisfy a first predetermined acceptance criterion, i.e., if the predicted motion response deviates too much from the actual motion response by the vehicle to a given control input, such as an applied steering angle change or a change in applied wheel torque. This way a reliable tyre explosion detection can be implemented at reasonable computational burden to the processing circuitry. The model-based method of detecting tyre explosion can advantageously be combined with other methods for detecting tyre explosion, such as wheel speed based methods that will be discussed in more detail below, and also methods based on TPMS sensor output. A number of control applications can be based on the tyre explosion detection mechanism to mitigate the consequences of the tyre explosion on, e.g., vehicle stability. Warning signals and notification messages in-between vehicle functional modules can be triggered in an automated and timely manner, which is an advantage. The tyre explosion detection functions are easily adapted to different types of vehicles, by changing the model of vehicle dynamics, which is an advantage. The model of vehicle dynamics used in the method may be selected from the many known models available in the literature. For instance, according to some aspects, the model of vehicle dynamics is any of a one-track vehicle dynamics model, a two-track vehicle dynamics model, and/or a look-up table of motion response by the heavy-duty vehicle to different control inputs. The control input considered by the tyre explosion function normally comprises an applied steering angle, since the response to an applied steering angle by most vehicles is significantly affected by an exploded tyre. This is because an exploded tyre has a reduced capability of Docket No.: P2022-1569 / P456436PC00 generating lateral force, which will show up as a difference between predicted vehicle motion response to the control input and actual vehicle motion response to the control input. The model of vehicle dynamics can be parameterized by vehicle longitudinal speed over ground. This data is normally available at the vehicle control system already, and it simplifies the modelling if the vehicle longitudinal speed over ground can be assumed known in the model, leading to a reduction in computational complexity. Vehicle longitudinal speed over ground can be obtained from many different sources, such as wheel speed sensors, global positioning system receivers, radar systems, and vision-based sensors. The model of vehicle dynamics is preferably also parameterized by front and rear axle stiffnesses which describe the tyre properties on the front axle and on the rear axle of the vehicle, allowing adaptation to different types of tyres. The wheelbase dimension, mass, and yaw inertia of the vehicle can also be used to parameterize the model. These as parameters all have an effect on the motion response by the vehicle to a control input, as will be elaborated upon below. It is an advantage that the tyre explosion detection functions discussed herein are easily adapted to different vehicle types, i.e., vehicles having different masses, wheelbase dimensions, and yaw inertias. Also, the tyre explosion detection functions are adaptable to changes in vehicle operating conditions in a straightforward manner. For instance, adaptation in response to a change in load are easily accommodated by many of the tyre explosion detection functions disclosed herein. The model of vehicle dynamics preferably has model state variables that at least comprise lateral speed and yaw rate. More advanced models comprising more state variables can of course also be used. However, it is an advantage that the technique performs well also with relatively simple models of vehicle dynamics. According to some aspects, the vehicle motion data comprises acceleration data obtained from one or more IMUs. IMU sensors provide reliable information on vehicle acceleration that can be compared against expected vehicle accelerations by the vehicle obtained from the model of vehicle dynamics. Other forms of yaw rate sensors can also be used, as well as other sensor systems on the vehicle, including vision-based sensors, radar sensors, and satellite positioning systems. The difference between the predicted motion response by the heavy-duty vehicle and the actual motion response by the heavy-duty vehicle may comprise any of a difference in yaw rate, a Docket No.: P2022-1569 / P456436PC00 difference in lateral speed rate of the front axle of the heavy-duty vehicle, and a difference in lateral vehicle front axle force. These three differences are preferably used jointly in the tyre explosion detection function for increased reliability. In this case the predetermined acceptance criterion can comprise a weighting of a plurality of difference metrics. The weighting is preferably also determined in dependence of an operating condition of the heavy-duty vehicle, as will be elaborated on below. Aspects of the disclosure also relates to processing circuitry configured to obtain wheel rotation data indicative of a first wheel rotary motion and of a second wheel rotary motion, for first and second wheels of an axle on the vehicle, or of a plurality of axles on the vehicle. The processing circuitry is configured to determine a difference in rotary motion between the first wheel rotary motion and the second wheel rotary motion, and to compensate the difference in rotary motion for a deviation in motion by the vehicle from a straight path. The processing circuitry is configured to detect tyre explosion in case the compensated difference in rotary motion does not satisfy a predetermined second acceptance criterion. This way tyre explosions can be detected with low latency and in a reliable and automated manner. The tyre explosion detection based on wheel rotary motion can be used separately from the methods based on the model of vehicle dynamics discussed above, i.e., as a stand-alone method for detection of tyre explosions, but the two methods in combination increase detection reliability. The first wheel rotary motion and the second wheel rotary motion may comprise wheel speed and/or wheel acceleration, which are measurements that can be obtained from wheel speed sensors in a cost-efficient and reliable manner. Wheel speed sensors are normally mounted on heavy-duty vehicles in use today. This is an advantage since many of the techniques and methods discussed herein can be implemented on computer systems of legacy vehicles, as a software update. The wheel speed data can also be used in the model-based method discussed above, e.g., to determine vehicle speed over ground in a reliable manner, since the data can be tagged with a likelihood of tyre explosion, in which case it should not be used in the model- based method. The deviation in motion by the vehicle from a straight path may comprise any of yaw motion and yaw motion rate indicative of a vehicle motion curvature. If the vehicle does not travel on a straight path, but along some form of curved track, then a difference in wheel rotary motion Docket No.: P2022-1569 / P456436PC00 of the left and right wheels of an axle is to be expected. Such expected differences in rotary motion should not be taken as an indication of tyre explosion, and it is therefore compensated before prior to detecting tyre explosion. The axle may be a steered axle on the vehicle, normally a steered front axle, although steered rear axles may also be relevant for tyre explosion detection according to the techniques discussed herein. The deviation in motion by the vehicle from the straight path then preferably comprises a steering angle applied at the steered axle. An applied steered angle indicates that a difference in rotary motion between the two wheels is to be expected. It is an advantage that such expected deviations from motion along a straight track is compensated for. According to some aspects, the processing circuitry is configured to receive acceleration data from one or more IMUs and/or steering angle data from a steering angle data source, indicative of a deviation in motion by the vehicle from a straight path. The option of obtaining motion data from several independent data sources means that a more reliable tyre explosion detection system can be realized, compared to a system which only uses data from a single source, such as only wheel speed sensor data, only IMU data, or only applied steering angle data. The processing circuitry is preferably also configured to determine a wheel motion oscillation based on the wheel rotation data, and to detect tyre explosion in case the compensated difference in rotary motion and/or the wheel motion oscillation does not satisfy predetermined acceptance criteria. Accounting for wheel oscillation in addition to other detection criteria gives a more reliable detection in many cases, and sometimes also a faster detection, which is an advantage. The processing circuitry, having access to wheel oscillation information, can also be configured to determine which wheel on the axle that has suffered a tyre explosion based on the wheel motion oscillation of the wheels on the axle. This information can be used when attempting to compensate for the impact on vehicle motion by the tyre explosion. According to some aspects, the processing circuitry is configured to verify a detected tyre explosion after a time period. It is desired to quickly detect tyre explosion, such that mitigating actions can be triggered without delay. However, the faster the detection is made, the more uncertain it normally is. The systems proposed herein may be configured to detect tyre explosion fast, and then to verify that the fast detection was actually correct after some delay. This gives fast detection, and also a reliable confirmation of the detection after some delay. Docket No.: P2022-1569 / P456436PC00 The processing circuitry can also be configured to compensate the difference in rotary motion for a difference in tyre radius on the left side and the right side on the axle. A difference in tyre radius will give rise to a constant or at least slowly changing difference in rotary motion. This bias in difference can be compensated for by the systems disclosed herein, which is an advantage. The processing circuitry is preferably configured to adjust vehicle motion in response to detecting a tyre explosion, regardless of how the tyre explosion was detected. An adjustment of vehicle motion may, e.g., comprise lowering vehicle speed in response to detecting a tyre explosion, and/or adjusting an admissible steering torque of the vehicle in response to detecting a tyre explosion. This way the computer system can mitigate the consequences of the tyre explosion, e.g., by compensating for introduced and undesired yaw motion. The heavy-duty vehicle may also comprise several motion support devices which can be coordinated to achieve motion in different ways. Steering can for instance be achieved using rear brake actuators as well as steered front wheels. The consequences of a tyre explosion on a front wheel of a steered axle can for instance be compensated for by applying a controlled amount of differential braking on the rear axles of the vehicle. The processing circuitry may also be configured to trigger generation of a warning signal to a driver of the vehicle in response to detecting a tyre explosion, and/or to trigger generation of a notification message to an autonomous drive system of the vehicle in response to detecting a tyre explosion, again regardless of how the tyre explosion was detected. This type of automated warning and/or notification improves vehicle safety. The processing circuitry is optionally also configured to activate a corrective steering function and/or an oversteer guidance system of the vehicle in response to detecting a tyre explosion. Hence, there are many ways in which the tyre explosion detector output can be used to mitigate the consequences of the tyre explosion on the motion of the vehicle, which is an advantage. According to some aspects, the processing circuitry is configured to determine a road surface roughness, and to discard a detected tyre explosion in case the road surface roughness does not satisfy a predetermined roughness acceptance criterion. This makes the system more robust on uneven road surfaces. Heavy-duty vehicles travelling on uneven roads often travel very slowly, where the consequences of tyre explosions are limited. Docket No.: P2022-1569 / P456436PC00 The different techniques and features of the computer system discussed herein may also be described as corresponding methods, associated with the same advantages. The above aspects, accompanying claims, and/or examples disclosed herein above and later below may be suitably combined with each other as would be apparent to anyone of ordinary skill in the art. Additional features and advantages are disclosed in the following description, claims, and drawings, and in part will be readily apparent therefrom to those skilled in the art or recognized by practicing the disclosure as described herein. There are also disclosed herein control units, computer systems, computer readable media, and computer program products associated with the above discussed technical benefits. BRIEF DESCRIPTION OF THE DRAWINGS With reference to the appended drawings, below follows a more detailed description of aspects of the disclosure cited as examples. Figure 1 illustrates an example heavy-duty vehicle, Figure 2 schematically shows wheels, sensors, and control units on a heavy-duty vehicle, Figure 3 illustrates an example model of vehicle dynamics, Figures 4-6 schematically illustrate aspects of an example vehicle control system, Figures 7A-C are graphs illustrating detection signals during a tyre explosion event, Figure 8 is a schematic diagram of an exemplary computer system, Figure 9 is a flow chart illustrating methods, and Figure 10 shows an example computer program product. DETAILED DESCRIPTION The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. The disclosure may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided for thoroughness and completeness. Like reference character refer to like elements throughout the description. Docket No.: P2022-1569 / P456436PC00 Aspects set forth below represent the necessary information to enable those skilled in the art to practice the disclosure. Figure 1 illustrates an example heavy-duty vehicle 100, here in the form of a truck comprising a tractor 110 and a trailer 120. The tractor 110 of the vehicle 100 comprises two front wheels 101 of a steered front axle F, where the left front wheel will be denoted 101L and the right front wheel will be denoted 101R below. The tractor 110 also comprises a set of rear wheels 102 on rear axles R1, R2. The trailer 120 also comprises wheels 103 arranged on axles T1, T2, T3. The present disclosure is applicable to many different vehicle types comprising steerable front wheels 101, not only articulated vehicles. Rigid trucks and other forms of heavy-duty vehicles are also covered by the teachings herein, as well as passenger cars and recreational vehicles. The principles of tyre explosion detection discussed herein are, however, particularly suitable for use with heavy-duty vehicles like that illustrated in Figure 1. The techniques for detecting tyre explosion discussed herein can be applied to any axle or axles on a vehicle, i.e., to a front axle, to a rear axle of a tractor unit 110, and/or to one or more axles of a trailer vehicle unit 120. Vehicle 100 comprises a computer-implemented control system arranged to control vehicle motion, among other things. This control system may comprise one or more control units 130 distributed over the vehicle or centralized at one place. Each vehicle control unit 130 may comprise one or more processor devices. A processor device may be distributed over several spatially separated units or centralized in one place. The control system, or parts thereof, may be arranged to communicate via wireless link 140 to a wireless access point 150, such as a radio base station of a cellular access network or the like. Thus, the vehicle control system may communicate with one or more remote servers 160 implementing data repositories, remote processing resources, and the like, in order to exchange data and perform various computation tasks. The vehicle control system 130 may be referred to as a system for vehicle motion management (VMM). Figure 2 schematically illustrates some components of an example heavy-duty vehicle 100. There is a front left wheel 101L and a front right wheel 101R arranged on the steered front axle F of the vehicle. The front axle F is normally not a physical axle connecting the two front Docket No.: P2022-1569 / P456436PC00 wheels, but an imaginary axis extending transversal to the vehicle longitudinal direction and intersecting the two front wheels 101L, 101R. The steered wheels 101L, 101R have respective steering angles ^_^ , ^_^ . These two angles may be assumed equal in most cases of relevance and will then be jointly denoted by ^. The front trackwidth of the vehicle 100 is denoted w. Each wheel 101L, 101R is associated with a wheel speed sensor WSFL 210 and WSFR 220. A wheel speed sensor may, e.g., comprise a Hall effect sensor or rotary encoder which measures the rotary motion of a wheel. There are also first and second rear axles R1, R2, with wheels 102. The index of a general rotation ^ of an object such as a wheel or a vehicle unit will be used herein to indicate which object the rotation refers to and about which axis. A wheel speed of the ^-th wheel on the vehicle about its wheel axle will be denoted ^_^ and its acceleration about the wheel axle ^̇_^, where ^ may, e.g., be ^^ for the front left wheel. A rotation of the vehicle 100 about an axis will be indicated by using the axis as subscript, i.e., ^_^ , ^_^ , ^_^ for rotation about axes x, y, and z. The x-axis extends in the longitudinal direction of the vehicle 100, the y-axis is lateral to the vehicle forward direction, and the z-axis is normal to the extension plane of the vehicle chassis. The meaning of a given rotation variable ^ will be clear from context. Yaw rate of the vehicle 100 about the center of gravity (CoG) will for instance normally be denoted ^_^ herein. A wheel speed sensor may be used to determine a wheel speed ^_^ of a wheel and/or a wheel acceleration ^̇_^, where ^̇ is generally used herein to denote the time derivative of the variable ^. Wheel speed sensors are generally known and will therefore not be discussed in more detail herein. There is also a steering angle data source 230 which provides data indicative of the respective steering angles ^_^ , ^_^ , or the common steering angle ^. The steering angle data source 230 may be a component in a power steering system or an encoder which provides data related to the current steered angle of the wheels 101L, 101R. The steering angle data source 230 may be part of an electronic power steering controller, or a module in the overall VMM system of vehicle 100. One or more inertial measurement units (IMU) 240 may be arranged to provide acceleration data. The data provided by the IMU may comprise accelerations in three dimensions, i.e., ^^_^ , ^_^ , ^_^^, and data indicative of the roll rate, pitch rate, and yaw rate, i.e., ^^_^ , ^_^, ^_^^ of the Docket No.: P2022-1569 / P456436PC00 vehicle 100, and sometimes also their respective time derivatives ^^̇_^, ^̇_^ , ^̇_^^. The location and orientation of each IMU on the vehicle frame can be assumed a-priori, which means that the output signal from a given IMU can be translated into a common reference system, perhaps one centered at the center of gravity (CoG) of the vehicle 100 and aligned with a forward direction of the vehicle 100. The location of a general sensor, such as an IMU, on a vehicle comprises information about where on the vehicle the sensor is located relative to some reference point on the vehicle, while the orientation comprises information about the rotation of the sensor in some reference system, e.g., the azimuth angle and the attitude angle of the sensor bore sight direction, or the rotation of the sensor reference system in relation to that of the vehicle. The vehicle 100 may also comprise one or more yaw rate sensors 260 integrated with the IMUs 240 or arranged as separate sensors. A yaw-rate sensor is a gyroscopic device that measures a vehicle's yaw rate, i.e., its angular velocity around some reference axis on the vehicle. There are two main types of yaw-rate sensors: the piezoelectric type and the micromechanical type. Advanced laser-based yaw-rate sensors are also being developed. The tyre explosion detection functions discussed herein can be used together with any type of yaw rate sensor. The wheel speed sensors 210, 220, the steering angle data source 230, and the one or more IMUs 240 are connected to the vehicle control unit 130 via wired or wireless link. The rear wheels 102 of the vehicle 100 may also be associated with respective optional wheel speed sensors 250 which are also connected to the control unit 130 (although the connections are not shown in Figure 2). One or more IMUs 240 may also be arranged in connection with the rear axles R1, R2 of the vehicle 100. The axles and wheels of the trailer vehicle unit 120 is not shown in Figure 2. It is, however, appreciated, that the techniques discussed herein for tyre explosion detection can also be applied to the wheels 103 and axles T1, T2, T3 of one or more trailer vehicle units and dolly vehicle units. It is known that a tyre explosion more or less immediately impacts the rotary motion of the wheel where the tyre explosion happened. Wheel rotary motion, such as wheel speed and wheel acceleration can therefore be used to detect when a tyre explosion occurs. However, wheel rotary motion also changes significantly during vehicle operation, e.g., as the vehicle Docket No.: P2022-1569 / P456436PC00 accelerates and decelerates. Yaw motion by the vehicle also has an impact on the rotary motion by two wheels on the same axle. It has been realized that by monitoring differences in wheel speed for two wheels on the same axle and compensating the difference in rotary motion of the wheels based on current vehicle motion, a robust tyre detection variable can be obtained which can be used for tyre explosion detection. Since wheel speed difference is monitored and not absolute wheel speed, the method becomes less sensitive for variation in longitudinal velocity by the vehicle. Any cornering by the vehicle is compensated for by the computer system, which means that the detection mechanism is able to cope also with significant yaw rate by the vehicle. To summarize, with reference also to Figure 8, which will be discussed in more detail below, there is disclosed herein a computer system 130, 800 for detecting tyre explosion in a heavy-duty vehicle 100. The computer system 130, 800 comprises processing circuitry, i.e., one or more control units, configured to obtain wheel rotation data indicative of a first wheel rotary motion ^_^, ^̇_^ and of a second wheel rotary motion ^_^ , ^̇_^, for first and second wheels 101L, 101R an axle F, R1, R2, T1, T2, T3 on the vehicle 100. The first wheel rotary motion ^_^ , ^̇_^ and the second wheel rotary motion ^_^, ^̇_^ may, e.g., comprise wheel speeds and/or accelerations obtained from respective wheel speed sensors 210, 220. Wheel speed oscillation is also considered a form of rotary motion herein. One or more axles may be considered in parallel by the computer system, where the steered front axle is often of most interest due to the impact on vehicle stability if a wheel on this axle explodes. The processing circuitry is also configured to determine a difference ∆^, ∆^̇ in rotary motion between the first wheel rotary motion ^_^, ^̇_^ and the second wheel rotary motion ^_^ , ^̇_^. This difference in rotary motion is indicative of how the first wheel rotates in comparison to the second wheel. In case the vehicle 100 travels along a straight path and on a smooth surface, there should only be a small difference between the two wheel speeds. An increase or a decrease in longitudinal speed by the vehicle will not be a problem since the difference in rotary motion will not be affected. However, if the vehicle is turning, i.e., moving along a path with a curvature, such as if the steering angles ^_^ , ^_^ on the front axle F are non-zero, then an expected difference in wheel rotary motion will be present, which should not trigger detection of tyre explosion. The processing circuitry is therefore configured to compensate the difference in rotary motion ∆^, ∆^̇ for a deviation in motion by the vehicle 100 from a straight path. After compensation, there should not be any significant difference left in the rotary motion of the Docket No.: P2022-1569 / P456436PC00 first and second wheels if all tyres are fully functional and no tyre has exploded. The processing circuitry is configured to detect tyre explosion in case the compensated difference in rotary motion ∆^, ∆^̇ does not satisfy a predetermined second acceptance criterion. The acceptance criteria may, e.g., comprise a threshold against which the compensated difference is compared. More advanced detection criteria can also be formulated, based on statistical analysis of the compensated difference. For instance, the compensated difference can be compared to an expected statistical distribution, and tyre explosion can be detected if the statistical distribution of the monitored compensated difference is no longer found to adhere to the expected statistical distribution. Aspects of time may also be added to the detection criteria. For instance, a filter bank can be implemented which low pass filters the compensated difference using two or more filter bandwidths, i.e., using two or more levels of averaging. Different thresholds can then be used for each filter in order to obtain a fast preliminary detection and a more reliable but higher latency detection. This filter bank can comprise any number of filters. The processing circuitry is optionally configured to verify a detected tyre explosion after a time period. This verification can, e.g., be based on the output of a low-pass filter or based on some other form of higher latency processing, such as a statistical test as discussed above, or the output from a Kalman filter or the like which is associated with higher latency compared to, e.g., faster threshold- based detectors. According to some aspects, the processing circuitry is also configured to compensate the difference in rotary motion ∆^, ∆^̇ for a difference in tyre radius on the left side and the right side on the axle. A difference in tyre radius will give a constant or slowly changing offset in rotary motion over the axle. The effects of tyre radius can be compensated for by high pass filtering the difference signal to remove “DC components”, i.e., constant differences which do not change fast over time. The constant difference in rotary motion can also be estimated, e.g., from low pass filtering the difference in rotary motion and then removing this difference during tyre explosion monitoring. A calibration error in, e.g., a wheel speed sensor, may also give a constant offset in measured rotary motion between the left wheel and the right wheel of an axle. All constant or slowly changing differences in rotary motion can be compensated for in this manner. The deviation in motion by the vehicle 100 from a straight path may comprises any of yaw motion ^_^, yaw motion rate ^̇_^, and/or steering angle ^ if the axle is a steered front or rear Docket No.: P2022-1569 / P456436PC00 axle. A vehicle model, such as a two-track model or the like, describing an expected motion by the vehicle in response to actuator commands and the like can be maintained and expected wheel speeds can be extracted from this model and used to compensate the difference in measured rotary motion by the wheels. The deviation in motion by the vehicle 100 from a straight path may also be obtained from a vehicle state estimation function comprised in the VMM function, as will be discussed in more detail below. Models of vehicle dynamics which can be used for this purpose are well known in the art and will therefore not be discussed in more detail herein. The processing circuitry may, for instance, be configured to receive acceleration data from one or more IMUs 240, and/or steering angle data from a steering angle data source 230, as discussed above. This data is indicative of a deviation in motion by the vehicle 100 from a straight path. The processing circuitry may also be configured to determine a wheel motion oscillation based on the wheel rotation data, and to detect tyre explosion in case the compensated difference in rotary motion ∆^, ∆^̇ and/or the wheel motion oscillation does not satisfy predetermined acceptance criteria. It has been observed that a wheel having suffered a tyre explosion will give rise to oscillations in rotary motion. This will be discussed in more detail below in connection to Figure 7C, where an example of such wheel rotary motion is illustrated. The oscillation is due to the wheel becoming uneven after a tyre explosion and engages the road surface differently over a rotation by the wheel. This uneven engagement with the road surface is often periodic in nature, and therefore gives rise to oscillation in the rotary motion by the wheel. Wheel motion oscillation can be determined using various methods. A preferred method is to count the time between each peak of the differential wheel speed (with or without compensation). Then, by inverting the average time between the peaks, the frequency in the time domain of the wheel oscillation is obtained in an approximate manner. Along with this, it is possible to compute a model-based wheel frequency based on an assumption of one impact per complete wheel revolution. A Fourier transform of the wheel speed data, or wheel speed difference data, can also be used to determine wheel motion oscillation. Wheel motion oscillation may comprise oscillation peaks, distribution of the frequency content in the wheel speed data, or the like. Docket No.: P2022-1569 / P456436PC00 The processing circuitry is optionally also configured to determine which wheel on the considered axle F, R1, R2, T1, T2, T3 that has suffered a tyre explosion based on the wheel motion oscillation of the wheels on the axle. A higher wheel motion oscillation is indicative of tyre explosion. Hence, if a tyre explosion is detected on a given axle, the oscillation behavior of the wheels on the axle can be considered. The wheel having the strongest oscillation behavior can then be identified and labelled as the wheel having suffered a tyre explosion. Of course, in rare events both tyres of an axle explode more or less simultaneously. In such cases the wheel identification method may declare that both wheels have suffered an explosion, by comparing the oscillation behavior to some form of detection criteria. The computer system may, for example, determine the principal frequency component of the wheel oscillation from a Fourier transform of the compensated wheel rotary motion difference data, and check to see if the frequency and magnitude of this principal component is indicative of tyre explosion. A unified tyre explosion detector may be designed which takes wheel speed, wheel acceleration, and wheel oscillation into account. A tyre explosion is then declared if a test statistic determined from a combination of the different data sources fails to meet a second acceptance criterion. For instance, suppose that ^_^ is a test statistic based on compensated wheel speed difference, ^_{^ ̇} is a test statistic on compensated wheel acceleration difference, and ^_^ is a based on oscillation in the rotary motion of a wheel, then a tyre explosion can be detected in case the test statistic ^ = ^_^^_^ + ^_{^ ̇}^_{^ ̇} + ^_^^_^ where ^_^, ^_{^ ̇}, ^_^ are having unit sum, fails to meet a second acceptance criterion, such as a predetermined threshold or predetermined statistical test. A tyre explosion can be detected with a given level of confidence. For instance, if the test statistic ^ > ^_^^ then a tyre explosion is possible. If the test statistic ^ > ^_^^ then a tyre explosion is likely, while if ^ > ^_^^ then a tyre explosion has definitely occurred. The thresholds ℎ1 < ℎ2 < ℎ3 can be predetermined values determined from practical experimentation of computer simulation. In some cases, there may be a small difference in the timing between the different test statistics ^_^ , ^_{^ ̇} and ^_^. To allow for such onset deviation, a sample and hold function can be added, a high value of the test statistic for some time. An example of such a function is a rate limiter filter. Another example is a function which Docket No.: P2022-1569 / P456436PC00 outputs the highest value seen over a time window, such as the highest value seen for a test statistic over the last 0.1 seconds or so. Another principle of tyre explosion detection will be described below, that is based on a comparison between a predicted motion response by the vehicle and an actual motion response by the vehicle. This method can also be incorporated into the unified tyre explosion detector to further increase reliability, as will be discussed below. An example derivation of the above tyre explosion detection method will now be given. To monitor differences in rotary motion between the front left wheel 101L and the front right wheel 101R a kinematic motion model associated with the vehicle 100 can be used. With reference to Figure 2, and neglecting lateral speed of the left front tyre, the translational hub speed ^_^^^^ is expressed as a longitudinal speed ^_^^^^ in the front left corner of the vehicle ^_^^^^ = ^_^^^^ cos(^_^) where ^_^ is the front left wheel ^_^ ≈ ^_^ , in which case a single steering angle value ^ can be used for both front wheels of the vehicle 100. A single steering angle value will be used from now on, to simplify the developments. Taking a vehicle rotation in the horizontal plane into account, the longitudinal corner speed is expressed as ^ ^_^^^^ = ^_^ − ^ 2 _^ Where ^_^ is the yaw motion of the vehicle (front) trackwidth, as indicated in Figure 2. The longitudinal speed of the vehicle at the center of gravity is denoted ^_^. Using the above relationships, the vehicle speed at the center of gravity, corrected for steering angle ^ and yaw motion ^_^ , is given by ^ ^_^ = ^_^^^^ + ^_^ In a similar way, the speed of as a function of the speed of the vehicle at the center of gravity ^ + ^ ^_{^^ ^} ^_^ ^_^^^^ = _^^ = 2 The front right wheel speed a function of the front left wheel speed ^_^^^^. Docket No.: P2022-1569 / P456436PC00 ^ ^ ^_^ ^ _^^^^ ^ ^^ ^ ^ + ^ cos(^) + ^ + ^_^ ^ ⋅ ^ ^ 2 2 2 ^ _^ _{^^^^ ^^^^} The relations between the translational hub speeds and the tyre angular speeds are ^_^^^^ = ^_^^^ ^_^^(1 − ^_^^^) ^_^^^^ = ^_^^^^_^^(1 − ^_^^^) where ^_^^^ , ^_^^^ are tyre effective radii, ^_^^ , ^_^^ are the angular wheel speeds, and ^_^^^ , ^_^^^ are the tyre longitudinal wheel slips. When wheel slips and tyre radii are the same for the two tyres, then the difference of the angular wheel speeds is manifested such as ^ ⋅ ^ ^ = ^ _^ _{^^ ^^} + cos This expression relates the rotary wheel to the rotary motion of the front right wheel, for a given road-to-wheel steering angle ^ and yaw motion ^_^ under the condition that wheel slips and effective tyre radii are the same or at least similar. Now, assume that the front right tyre explodes. In this situation the tyre will be exposed to severe disturbances. Both the tyre radius and the wheel slip of the exploded tyre will most likely be rapidly changed and different from the unaffected left tyre. Hence, if the left wheel rotary motion is used to estimate the expected right wheel rotary motion, ^ ⋅ ^ ^ = ^ _^ _{^^ ^^} + cos A difference in rotary motion motion and the second wheel rotary motion can, for instance, be quantified as ^ ⋅ ^ Δ^ = ^ − ^ _^ _{^^ ^^} = ^_^^ − ^^_^^ + ^ cos In case the axle is not Figure 3 illustrates an example model of vehicle dynamics 300, in this case a one-track model where the vehicle is modelled as having one front wheel 310 and one rear wheel 320. The front wheel is representative of the wheels on the front axle of the vehicle, and the rear wheel is representative of the rear wheels on the vehicle. The steering angle of the front axle is denoted by ^. The vector ^_^ in Figure 3 denotes the velocity of the front axle. It has a longitudinal component ^_^ and a lateral component ^_^^ (indicating that it is the lateral speed component of the front axle). The angle of the front axle speed vector ^_^ relative to the longitudinal direction Docket No.: P2022-1569 / P456436PC00 of the vehicle is denoted by ^_^ . The difference between ^_^ and ^ is the front axle slip angle, and it is denoted by ^_^ in Figure 3. Similar notation is for the rear axle, i.e., the vector ^_^ in Figure 3 denotes the velocity vector of the rear axle. It has a longitudinal component ^_^ and a lateral component ^_^^ . The angle of vector ^_^ relative to the longitudinal direction is denoted by ^_^ . The center of gravity (CoG) of the vehicle is also indicated in Figure 3. At this point the longitudinal velocity vector is ^, with a longitudinal component ^_^ and a lateral component ^_^, with angle ^ relative to the longitudinal direction. The yaw rate about the CoG is in Figure 3. The lateral front axle force is denoted ^_^^ and the lateral rear axle force is denoted ^_^^. The vehicle wheelbase dimensions are represented in Figure 3 by the distance ^_^ from the front axle to the CoG and by the distance ^_^ from the rear axle to the CoG. The combined slip stiffness of the wheels on the front axle is denoted ^_^ and the combined slip stiffness of the wheels on the front axle is denoted ^_^ . The vehicle mass is denoted by ^. The acceleration by the vehicle in the lateral direction is denoted by ^_^, and the yaw inertia of the vehicle is denoted by ^_^ . With this notation, the following relationships can be formulated. It is appreciated that these relationships are approximative, but normally come close to the true relationships during most maneuvers. ^^_^ = ^^^̇_^ + ^_^^_^^ = ^_^^ cos(^ )+ ^_^^ ≈ ^_^^+ ^_^^ The main input angle ^. The state variables of the model are the lateral speed ^_^ and the yaw rate ^_^ . Note that the vehicle speed over ground ^_^ is considered as a parameter in the model. A model of vehicle dynamics can, Docket No.: P2022-1569 / P456436PC00 generally, be adapted to more axles, for example two rear axles. It can also we expanded to cover one or more trailer units. The model of vehicle dynamics can also be expanded with more inputs, for example wheel individual torque actuation which impact the yaw acceleration, or other steerable axles. A large number of models of vehicle dynamics, of varying complexity and accuracy, are known in the art. Models of vehicle dynamics will therefore not be discussed in more detail herein. The techniques for detecting tyre explosion discussed herein are applicable together with most known models of vehicle dynamics. A number of interesting indicators of motion behavior can be derived from a model like that illustrated in Figure 3. The time derivative of lateral velocity in the center of gravity is for instance expressed as ^̇_^ = ^_^ − ^_^^_^ Where ^_^ is the lateral acceleration in the center of gravity, ^_^ is the vehicle longitudinal speed, and ^_^ is the vehicle yawrate. The time derivative of the lateral speed of the front axle, i.e., the lateral speed rate ^̇_^^ of the front axle is ^̇_^^ = ^_^ − ^_^^_^ + ^_^^̇_^ It has been found that this part changes significantly when a tyre explosion occurs. Hence, by comparing sensor data indicative of the front axle lateral speed rate ^̇_^^ to the lateral speed rate predicted by the model of vehicle dynamics, tyre explosion can be detected. The lateral acceleration ^_^ can be measured by, e.g., an IMU, ^_^ can be obtained from a wheel speed sensor or from some other sensor system arranged to measure speed over ground, and ^_^ can be obtained from a yaw rate sensor. Thus, the front axle lateral speed rate ^̇_^^ in response to a control input can be both predicted by a model of vehicle dynamics and evaluated from sensor measurements. By Newtons second law in combination with a lateral force and yaw moment equilibrium, one obtains the relationships: ^_^^ + ^_^^ = ^^_^ ^_^^_^^ − ^_^^_^^ = ^_^^̇_^ Looking at the vehicle frame reference system, the lateral front axle force is then Docket No.: P2022-1569 / P456436PC00 ^ ^̇ + ^ ^^ ^ = _{^ ^ ^ ^} _^^ This quantity has also been found explosion. Hence, by monitoring the lateral front axle force using a model of vehicle dynamics, and also using sensor measurements, a tyre explosion can be detected. The difference in predicted yaw rate ^_^ by the model of vehicle dynamics and the actual yaw rate measured by the one or more yaw rate sensors on the vehicle is also indicative of tyre explosion. To summarize, at least three different submodules can be implemented by a computer system 130, 800 for detecting tyre explosion in a heavy-duty vehicle 100. Example submodule 1: Yaw rate (^_^) residual. From model: The yaw rate is computed from model by input steering angle to the one-track model. One can use a Kalman filter here, or implement a digital twin of the vehicle simulating the expected yaw rate. From measurements: The state yaw rate is taken directly from the measurement of yaw rate. Detection example: explosion is true if ^^^^^_^,^^^^^ − ^_^,^^^^ > ^_^, where ^_^ is some form of predetermined acceptance criterion, Example submodule 2: Lateral front axle speed rate (^̇_^^) residual. From model: The one-track model is used (with steering angle as an input) to compute ^_^ and ^_^ . The lateral acceleration is related to lateral front axle speed rate and yaw rate as ^_^ = ^_{^ ̇} + ^_^^_^ . From measurements: The lateral acceleration ^_^ can be measured by an IMU, the yaw rate ^_^ can be measured by a yaw rate sensor, and ^̇_^ is the time derivative of the yaw rate measurement. Detection example: explosion is true if ^^^^^̇_^^,^^^^^ − ^̇_^^,^^^ ^ > ^_^, where ^_^ is some form of predetermined acceptance criterion, such as a threshold value. Example submodule 3: Lateral front axle force (^_^^) residual. Docket No.: P2022-1569 / P456436PC00 From model: ^̇_^ and ^_^ are extracted from the model of vehicle dynamics. From measurement: ^̇_^ and ^_^ are obtained from the IMU. Detection example: explosion is true if ^^^^^_^^,^^^^^ − ^_^^,^^^ ^ > ^_^, where ^_^ is some form of predetermined acceptance criterion, For increased tyre explosion detection robustness, the outputs of the difference comparisons can be weighted together to form a joint likelihood of tyre explosion ^, i.e., ^ = ^ ^_^^_^ where ^_^ is the weighting factor of and where ^_^ is the test statistic of the ^-th submodule. The result of the tyre explosion detection based on wheel speed data discussed above can also be incorporated into a joint tyre explosion detection function. To summarize, with reference also to Figure 4 and to Figure 8, tyre explosion in a heavy-duty vehicle 100 can be detected by a computer system 130, 800 comprising processing circuitry configured to obtain control input data indicative of a control input 475 to one or more MSDs 430 of the heavy-duty vehicle 100, i.e., a control command sent to the vehicle steering actuators or other MSDs. The processing circuitry if configured to obtain a model 300 of vehicle dynamics configured to predict a motion response by the heavy-duty vehicle 100 to a control input. The model of vehicle dynamics may be loaded from memory or constructed by the vehicle in real time as the vehicle operates. A low complexity model such as the one-track model 300 discussed above can be used for this purpose, and more advanced vehicle models can also be used. The processing circuitry, having the model of vehicle dynamics and the control input, can then predict a motion response by the heavy-duty vehicle 100 to the control input 475 using the model 300 of vehicle dynamics. In other words, the processing circuitry can determine what the expected motion response by the vehicle is, given that all is well, and the vehicle behaves “normally”. The processing circuitry is also configured to obtain vehicle motion data 445 from a sensor system 440 of the heavy-duty vehicle 100, such as the one or more IMUs 240 and/or yaw rate sensors 260. Motion data can also be obtained from other sensor systems, such as vision-based sensors, radar sensors, and global positioning system receivers in a known manner. This sensor data is indicative of an actual motion response by Docket No.: P2022-1569 / P456436PC00 the heavy-duty vehicle 100 to the control input 475, i.e., the sensor data describes how the vehicle actually moves in response to, e.g., an applied steering angle. Thus, the processing circuitry has an idea of what the expected motion by the vehicle is (from the model of vehicle dynamics), and also what the actual motion by the vehicle is (from the sensor systems on the vehicle). This allows the processing circuitry to detect tyre explosion in case a difference between the predicted motion response by the heavy-duty vehicle 100 and the actual motion response by the heavy-duty vehicle 100 does not satisfy a first predetermined acceptance criterion. This first predetermined acceptance criterion can be just a straightforward threshold ^_^, ^_^, ^_^ as discussed above, or a more complicated acceptance criterion based on some form of statistical test. The first predetermined acceptance criterion can, for instance, be based on statistical analysis of the difference between the predicted and the actual vehicle motion in response to the control input. For instance, the difference can be compared to an expected statistical distribution, and tyre explosion can be detected if the statistical distribution of the difference between predicted and actual vehicle motion is no longer found to adhere to the expected statistical distribution. Aspects of time may also be added to the detection criteria. For instance, a filter bank can be implemented which low pass filters the difference between the predicted motion response by the heavy-duty vehicle 100 and the actual motion response by the heavy-duty vehicle 100 using two or more filter bandwidths, i.e., using two or more levels of averaging. Different thresholds can then be used for each filter in order to obtain a fast preliminary detection and a more reliable but higher latency detection. This filter bank can comprise any number of filters. The processing circuitry is optionally configured to verify a detected tyre explosion after a time period. This verification can, e.g., be based on the output of a low-pass filter or based on some other form of higher latency processing, such as a statistical test as discussed above, or the output from a Kalman filter or the like which is associated with higher latency compared to, e.g., faster threshold-based detectors. The model of vehicle dynamics used to get an idea of the expected vehicle behavior to the control input can be any of a one-track vehicle dynamics model, a two-track vehicle dynamics model, and/or a look-up table of motion responses by the heavy-duty vehicle 100 to different control inputs. Other models can also be used. The important point of the vehicle dynamics model is that is accepts a current control input and predicts the response by the vehicle to the control input. The perhaps most important control input for detecting tyre explosion on a front Docket No.: P2022-1569 / P456436PC00 axle of the vehicle is often the applied steering angle ^, but other control inputs may also be relevant, such as applied torques on different wheels, wheel slip values, generated tyre forces in the wheel coordinate systems, and so on. It is appreciated that the model of vehicle dynamics 300 can be parameterized in different ways, and that more complex models of vehicle dynamics often have more parameters compared to less complex models of vehicle dynamics. The vehicle speed over ground ^_^ is often an important parameter in a model of vehicle dynamics. The model of vehicle dynamics 300 may furthermore be parameterized by front and rear axle stiffnesses ^_^ , ^_^ , vehicle wheelbase dimensions ^_^ , ^_^ , vehicle mass ^, and vehicle yaw inertia ^_^ . The model of vehicle dynamics 300 preferably comprises a plurality of state variables, such as lateral speed ^_^ and yaw rate ^_^ of the vehicle 100. The more complex the model of vehicle dynamics is, the more state variables it normally has. The model of vehicle dynamics can be set up to model a single vehicle unit, such as the tractor 110, or more than one vehicle unit 110, 120 in a vehicle combination such as that illustrated in Figure 1. The difference between the predicted motion response by the heavy-duty vehicle 100 and the actual motion response by the heavy-duty vehicle 100 may as discussed above comprise a difference in predicted and actual yaw rate ^_^. In other words, the processing circuitry uses the control input and the model of vehicle dynamics to predict what the yaw rate should have been given the current vehicle state and model parameters such as longitudinal velocity. The processing circuitry then compares this predicted yaw rate with a yaw rate measured by some type of yaw rate sensor, such as an IMU 240. A difference between predicted and measured yaw rate may be indicative of a tyre explosion. The difference between predicted motion response by the heavy-duty vehicle 100 and actual motion response by the heavy-duty vehicle 100 may also comprise a difference in lateral speed rate ^̇_^ of the front axle of the heavy-duty vehicle 100. As for yaw rate, the lateral speed rate ^̇_^ can be predicted by the model of vehicle dynamics and at the same time measured by one or more vehicle sensors. A difference between predicted lateral speed rate ^̇_^ and measured lateral speed rate ^̇_^ is indicative of a tyre explosion and can therefore be used by the processing circuitry to detect when tyre explosion occurs. Docket No.: P2022-1569 / P456436PC00 The difference between the predicted motion response by the heavy-duty vehicle 100 and the actual motion response by the heavy-duty vehicle 100 may furthermore comprise a difference in lateral vehicle front axle force ^_^^ . Again, the predicted lateral vehicle front axle force is compared to an actual lateral vehicle front axle force, and if the difference does not satisfy an acceptance criterion, then tyre explosion is declared. The predetermined acceptance criterion preferably comprises a weighting of a plurality of difference metrics, as will be discussed in more detail below in connection to Figure 6, where the weighting is preferably determined in dependence of an operating condition of the heavy- duty vehicle 100. Figure 4 schematically illustrates functionality 400 for controlling the vehicle 100 by some example motion support devices (MSD) here comprising brake actuators, propulsion actuators, and power steering, with respective controllers collectively referred to in Figure 3 as MSD control 430. A traffic situation management (TSM) function 410 plans driving operation with a time horizon of 10 seconds or so. This time frame corresponds to, e.g., the time it takes for the vehicle 100 to negotiate a curve or the like. The vehicle maneuvers, planned and executed by the TSM function 410, can be associated with acceleration profiles areq and curvature profiles c_req which describe a desired target vehicle velocity in the vehicle forward direction and turning to be maintained for a given maneuver. The TSM function continuously requests the desired acceleration profiles areq and steering angles (or curvature profiles creq) from the VMM system 420 which performs force allocation to meet the requests from the TSM function in a safe and robust manner. The VMM system 420 operates on a timescale of below one second or so and will be discussed in more detail below. Each wheel 102 on the vehicle has a longitudinal velocity component ^_^ and a lateral velocity component ^_^ (in the coordinate system of the wheel or in the coordinate system of the vehicle, depending on implementation). There is a longitudinal wheel force Fx and a lateral wheel force F_y, and also a normal force F_z acting on the wheel (not shown in Figure 3). Unless explicitly stated otherwise, the wheel forces are defined in the coordinate system of the wheel, i.e., the longitudinal force is directed in the rolling plane of the wheel, while the lateral wheel force is directed normal to the rolling plane of the wheel. The ^-th wheel 101, 102 on the vehicle 100 Docket No.: P2022-1569 / P456436PC00 has a rotational velocity ^_^, and a tyre radius ^_^ . The tyre radius may be specified in terms of an effective rolling radius of the wheel. With continued reference to Figure 4, the TSM function 410 generates vehicle motion requests which may comprise a desired curvature c_req to be followed by the vehicle, and desired vehicle unit accelerations a_req. Given the discussion above, it is appreciated that the motion request will have an impact on the expected nominal difference in tyre rotary motion. The VMM system 420 operates with a time horizon of about 1 second or so, and continuously transforms the acceleration profiles areq and curvature profiles creq from the TSM function 410 into control commands 431, 432, 433 for controlling vehicle motion functions, actuated by the different MSDs of the vehicle 100 which report back capabilities 434, 435, 436 to the VMM function 420, which in turn may be used as constraints in the vehicle control. The VMM system 420 performs vehicle state or motion estimation 450, i.e., the VMM system 420 continuously determines a vehicle state s as function of time t comprising positions, speeds, accelerations, and articulation angles of the different units in the vehicle combination by monitoring operations using various sensors 440 arranged on the vehicle 100, often but not always in connection to the MSDs. An important input to the state estimation 450 may of course be the signals from the vehicle speed sensor and the wheel speed sensors on the heavy-duty vehicle 100. The vehicle state at a future time instant can also be predicted by a state prediction function 455. This vehicle state prediction function may be realized by a vehicle model having a vehicle state which can be extrapolated into a predicted vehicle state, given a current vehicle state, and optionally also given the current vehicle motion request. The state estimation function 450 may be used to determine the deviation in motion by the vehicle 100 from a straight path, used by the tyre explosion monitor 480. The result of the state estimation 450 and optionally also the state prediction 455, i.e., the estimated vehicle state s at one or more time instants, is input to a force generation module 460 which determines the required global forces V=[V1, V2] for the different vehicle units to cause the vehicle 100 to move according to the requested acceleration and curvature profiles a_req, c_req, and to behave according to the desired vehicle behavior. This example has two vehicle units. More vehicle units are possible, and also a single vehicle unit, e.g., in case the vehicle is a rigid truck or a passenger car. The required global force vector V is input to an MSD coordination Docket No.: P2022-1569 / P456436PC00 function 470 which allocates wheel forces and coordinates other MSDs such as steering and suspension. The MSD coordination function outputs an MSD control allocation for the i:th wheel, which may comprise any of a torque Ti, a longitudinal wheel slip ^i, a wheel rotational speed ^_i, and/or a wheel steering angle ^_i. The coordinated MSDs then together provide the desired lateral Fy and longitudinal Fx forces on the vehicle units, as well as the required moments Mz, to obtain the desired motion by the vehicle combination 100. Thus, according to some aspects of the present disclosure, the VMM system 420 manages both force generation and MSD coordination, i.e., it determines what forces that are required at the vehicle units in order to fulfil the requests from the TSM function 410, for instance to accelerate the vehicle according to a requested acceleration profile requested by TSM and/or to generate a certain curvature motion by the vehicle also requested by TSM. The forces may comprise e.g., yaw moments Mz, longitudinal forces Fx and lateral forces Fy, as well as different types of torques to be applied at different wheels. The forces are determined such as to generate the vehicle behavior which is expected by the TSM function in response to the control inputs generated by the TSM function 410. A tyre explosion monitor 480 according to the teachings herein is comprised in the VMM function 420. The tyre explosion monitor may be based solely on the principles of monitoring a compensated difference in rotary motion of the wheels on the vehicle 100, solely on the principles of monitoring the difference between predicted motion by the vehicle 100 and the actual motion by the vehicle 100 in response to a given control input or based on a combination of the two principles. The tyre explosion monitor 480 receives sensor data 445 from the sensors 440 and performs one or more of the above discussed methods for detecting tyre explosions. The output of the tyre explosion monitor 480 may be sent to the state estimation function 450 and/or to the state prediction function 455, where it can be used to adjust the estimated vehicle state to account for the tyre explosion. The output from the tyre explosion monitor 480 may also be useful at the MSD coordination function 470, since a wheel associated with a tyre explosion will have a reduced capability of generating wheel force. Hence, wheel forces should not be assigned to a wheel having an exploded tyre. The output of the tyre explosion monitor 480 may also be sent directly to one or more MSD controllers, bypassing higher layer controls. The MSD controller Docket No.: P2022-1569 / P456436PC00 may respond faster to a detected tyre explosion, similar to when the human brain is bypassed if a hand is burned on the stove, to more quickly remove the hand from the heat source. The techniques for tyre explosion detection discussed herein may, generally, be applied in a number of vehicle control functions. For instance, the processing circuitry executing the tyre explosion detection routines may also be configured to adjust vehicle motion in response to detecting a tyre explosion, to lower vehicle speed in response to detecting a tyre explosion, and/or to adjust an admissible steering torque of the vehicle 100 in response to detecting a tyre explosion. The processing circuitry may also be configured to trigger generation of a warning signal 485 to a driver of the vehicle 100 in response to detecting a tyre explosion, as well as to trigger generation of a notification message 485 to an autonomous drive system of the vehicle 100 in response to detecting a tyre explosion. The processing circuitry is optionally also configured to activate a corrective steering function and/or an oversteer guidance system of the vehicle 100 in response to detecting a tyre explosion. Some road surfaces may be less even than others. To accommodate uneven road surfaces, the processing circuitry may be arranged to adjust a degree of low pass filtering of sensor signals in dependence of the road surface roughness, such that more filtering is applied when the road surface is rough compared to when it is smooth. The road surface roughness can be determined based on the output from the one or more IMUs 240, e.g., as a root-mean-squared (RMS) value of measured acceleration, which will be indicative of vibration experienced by the wheels on vehicle 100. Wheel suspension sensors can also be used to determine if the road surface is even or if there are significant unevenness in the road surface. Suspension bellow pressure sensors can, e.g., be used for this purpose. A suitable degree of low pass filtering (a suitable filtering bandwidth) for a given surface roughness can be determined from practical experimentation, laboratory experimentation, or from computer simulation. The acceptance criteria used to detect tyre explosion can of course also be adjusted in dependence of the road surface roughness, e.g., by increasing detection thresholds or accounting for an increased amount of disturbance due to road surface unevenness. A detection threshold forming part of the first or the second acceptance criterion may, e.g., be configured as an increasing function of the RMS value of measured acceleration. Docket No.: P2022-1569 / P456436PC00 According to some aspects, the processing circuitry is configured to determine a road surface roughness, e.g., using an IMU, and to discard a detected tyre explosion in case the road surface roughness does not satisfy a predetermined roughness acceptance criterion. Figure 5 provides a schematic overview 500 of an example tyre explosion detector based on wheel rotational behavior. A vehicle controller 130 controls the vehicle 100 by sending control signals 501 to control, e.g., wheel forces as discussed above. A sensor system 540 monitors vehicle behavior, and outputs sensor signals 502 to the tyre explosion detector system 503. The tyre explosion detector system 503 consists of a number of optional modules, where each module is arranged to determine a difference in rotary motion between the first wheel rotary motion and the second wheel rotary motion. A wheel speed difference module 510 is arranged to determine a wheel speed difference ∆^. A wheel acceleration difference module 520 is arranged to determine a wheel acceleration difference ∆^̇. A wheel oscillation frequency computation module 530 is arranged to determine a wheel motion oscillation. The outputs from the respective modules are sent to a detector module 540, which performs a test on the signals from the modules 510, 520, 530 to determine if a compensated difference in rotary motion satisfies a predetermined second acceptance criterion or not. The result of this test is forwarded to the vehicle controller 130 as a tyre explosion detection signal 504. Figure 6 provides a schematic overview 600 of another example tyre explosion detector based on predicted and actual vehicle motion response to a control input 601, such as an applied steering angle and/or an applied wheel torque. A model of vehicle dynamics 300 is executed by the tyre explosion detector. This model 300 was discussed above, where it was noted that it can vary in both complexity and modelling principles between different implementations. A one-track model is often sufficient, but more advanced two-track models can also be used. A database of previously experienced vehicle responses to a control input can also be maintained and used as model of vehicle behavior. An advantage of using this type of database for recording vehicle motion behavior in response to control inputs, given a current vehicle state, has the advantage of being possible to tailor to a specific vehicle, but the amount of data may be prohibitively large. The output of the model 300 is a predicted response by the vehicle 100 to a given control input, such as an applied steering angle. This predicted motion response by the vehicle is in this Docket No.: P2022-1569 / P456436PC00 example sent to three different sub-modules, a yaw rate residual monitor 610, a lateral front axle speed rate residual monitor 620, and a lateral front axle force residual monitor 630. Vehicle motion data 445 from a sensor system 440 of the heavy-duty vehicle 100 is also obtained. This motion data is indicative of an actual motion response by the heavy-duty vehicle 100 to the control input 601. The different monitors 610, 620, 630 all output respective differences between predicted motion response by the heavy-duty vehicle and actual motion response by the heavy-duty vehicle to a detector function 640 which compares the monitored differences to one or more acceptance criteria, such as predetermined thresholds. More advanced acceptance criteria may, e.g., comprise various statistical tests and ranges. One acceptance criterion may, e.g., comprise allowing a difference to exceed a threshold value for a limited amount of time, and declaring a tyre explosion in case the difference exceeds a threshold for a time period. The detector function 640 preferably considers the different outputs from the sub modules 610, 620, 630 jointly as discussed above. The output from the detector 603 is then sent to the vehicle controller 130. It is noted that the vehicle controller may receive tyre explosion detection data from a detector based on wheel speeds as in Figure 5 at the same time as it receives tyre explosion data from a model-based tyre explosion detector as exemplified in Figure 6. The vehicle controller can then use both data sources to detect tyre explosions with increased reliability as a result. Figure 7A shows a times series of the residual angular wheel speed evolves during an explosion. From the figure, it is evident the amplitude changes after the explosion. The magnitude of this signal can therefore be used for tyre explosion detection. A large differential wheel acceleration indicates an influence of an external force or that the tyre radius changes quickly. The entity is computed by taking the time derivative of Δ^ to get Δ^̇. This signal is exemplified in Figure 7B. From the plots 710, 720 in Figure 7A and in Figure 7B it is evident that following the tyre explosion: - The magnitude of wheel speed difference increases, - The magnitude of the wheel speed differential acceleration increases, - The differential wheel speed oscillates with large amplitude and high frequency. Figure 7C illustrates a characteristics oscillation behavior 530 due to tyre explosion. Docket No.: P2022-1569 / P456436PC00 The reason for having three modules is that, depending on the driving situation, they can have various accuracy. For example, during curve driving the lateral force module (no 3) is expected to be more efficient. Hence the weights are suggested to be a function of speed and curvature. Figure 8 is a schematic diagram of a computer system 800 for implementing examples disclosed herein. The computer system 800 is adapted to execute instructions from a computer- readable medium to perform these and/or any of the functions or processing described herein. The computer system 800 may be connected (e.g., networked) to other machines in a LAN, an intranet, an extranet, or the Internet. While only a single device is illustrated, the computer system 800 may include any collection of devices that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. Accordingly, any reference in the disclosure and/or claims to a computer system, computing system, computer device, computing device, control system, control unit, electronic control unit (ECU), processor device, etc., includes reference to one or more such devices to individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. For example, a control system may include a single control unit, or a plurality of control units connected or otherwise communicatively coupled to each other, such that any performed function may be distributed between the control units as desired. Further, such devices may communicate with each other or other devices by various system architectures, such as directly or via a Controller Area Network (CAN) bus, etc. The computer system 800 may comprise at least one computing device or electronic device capable of including firmware, hardware, and/or executing software instructions to implement the functionality described herein. The computer system 800 may include a processor device 802 (may also be referred to as a control unit), a memory 804, and a system bus 806. The computer system 800 may include at least one computing device having the processor device 802. The system bus 806 provides an interface for system components including, but not limited to, the memory 804 and the processor device 802. The processor device 802 may include any number of hardware components for conducting data or signal processing or for executing computer code stored in memory 804. The processor device 802 (e.g., control unit) may, for example, include a general-purpose processor, an application specific processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a circuit containing processing components, a group of Docket No.: P2022-1569 / P456436PC00 distributed processing components, a group of distributed computers configured for processing, or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The processor device may further include computer executable code that controls operation of the programmable device. The system bus 806 may be any of several types of bus structures that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and/or a local bus using any of a variety of bus architectures. The memory 804 may be one or more devices for storing data and/or computer code for completing or facilitating methods described herein. The memory 804 may include database components, object code components, script components, or other types of information structure for supporting the various activities herein. Any distributed or local memory device may be utilized with the systems and methods of this description. The memory 804 may be communicably connected to the processor device 802 (e.g., via a circuit or any other wired, wireless, or network connection) and may include computer code for executing one or more processes described herein. The memory 804 may include non-volatile memory 808 (e.g., read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.), and volatile memory 810 (e.g., random-access memory (RAM)), or any other medium which can be used to carry or store desired program code in the form of machine- executable instructions or data structures, and which can be accessed by a computer or other machine with a processor device 802. A basic input/output system (BIOS) 812 may be stored in the non-volatile memory 808 and can include the basic routines that help to transfer information between elements within the computer system 800. The computer system 800 may further include or be coupled to a non-transitory computer- readable storage medium such as the storage device 814, which may comprise, for example, an internal or external hard disk drive (HDD) (e.g., enhanced integrated drive electronics (EIDE) or serial advanced technology attachment (SATA)), HDD (e.g., EIDE or SATA) for storage, flash memory, or the like. The storage device 814 and other drives associated with computer- readable media and computer-usable media may provide non-volatile storage of data, data structures, computer-executable instructions, and the like. Docket No.: P2022-1569 / P456436PC00 A number of modules can be implemented as software and/or hard coded circuitry to implement the functionality described herein in whole or in part. The modules may be stored in the storage device 814 and/or in the volatile memory 810, which may include an operating system 816 and/or one or more program modules 818. All or a portion of the examples disclosed herein may be implemented as a computer program product 820 stored on a transitory or non-transitory computer-usable or computer-readable storage medium (e.g., single medium or multiple media), such as the storage device 814, which includes complex programming instructions (e.g., complex computer-readable program code) to cause the processor device 802 to carry out the steps described herein. Thus, the computer-readable program code can comprise software instructions for implementing the functionality of the examples described herein when executed by the processor device 802. The processor device 802 may serve as a controller or control system for the computer system 800 that is to implement the functionality described herein. The computer system 800 also may include an input device interface 822 (e.g., input device interface and/or output device interface). The input device interface 822 may be configured to receive input and selections to be communicated to the computer system 800 when executing instructions, such as from a keyboard, mouse, touch-sensitive surface, etc. Such input devices may be connected to the processor device 802 through the input device interface 822 coupled to the system bus 806 but can be connected through other interfaces such as a parallel port, an Institute of Electrical and Electronic Engineers (IEEE) 1394 serial port, a Universal Serial Bus (USB) port, an IR interface, and the like. The computer system 800 may include an output device interface 824 configured to forward output, such as to a display, a video display unit (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 800 may also include a communications interface 816 suitable for communicating with a network as appropriate or desired. Figure 9 is a flow chart illustrating methods that correspond to the different technical features of the computer system and the vehicles discussed herein. The flow chart illustrates a computer- implemented method for detecting tyre explosions in a heavy-duty vehicle 100. The method comprises: Docket No.: P2022-1569 / P456436PC00 obtaining S1 control input data indicative of a control input 475 to one or more MSDs 430 of the heavy-duty vehicle 100, obtaining S2 a model 300 of vehicle dynamics configured to predict a motion response by the heavy-duty vehicle 100 to a control input, predicting S3 a motion response by the heavy-duty vehicle 100 to the control input 475 using the model 300 of vehicle dynamics, obtaining S4 vehicle motion data 445 from a sensor system 440 of the heavy-duty vehicle 100 indicative of an actual motion response by the heavy-duty vehicle 100 to the control input 475, and detecting S5 tyre explosion in case a difference between the predicted motion response by the heavy-duty vehicle 100 and the actual motion response by the heavy-duty vehicle 100 does not satisfy a first predetermined acceptance criterion. The method optionally comprises obtaining S6, by processing circuitry of a computer system, wheel rotation data indicative of a first wheel rotary motion ^_^ , ^̇_^ and of a second wheel rotary motion ^_^, ^̇_^, for first and second wheels 101L, 101R, 102, 103 of an axle F, R1, R2, T1, T2, T3 on the vehicle 100. The method also comprises determining S7, by the processing circuitry, a difference ∆^, ∆^̇ in rotary motion between the first wheel rotary motion ^_^, ^̇_^ and the second wheel rotary motion ^_^, ^̇_^, as well as compensating S8, by the processing circuitry, the difference in rotary motion ∆^, ∆^̇ for a deviation in motion by the vehicle 100 from a straight path. The method also comprises detecting S9, by the processing circuitry, tyre explosion in case the compensated difference in rotary motion ∆^, ∆^̇ does not satisfy a second predetermined acceptance criterion. It is noted that the tyre explosion detection method based on a compensated difference in rotary motion can be performed independently of the tyre explosion detection method based on modelled and measured vehicle response to a control input. In other words, there is also disclosed herein a computer-implemented method for detecting tyre explosion in a heavy-duty vehicle 100 that comprises obtaining S6, by processing circuitry of a computer system, wheel rotation data indicative of a first wheel rotary motion ^_^ , ^̇_^ and of a second wheel rotary motion ^_^, ^̇_^, for first and second wheels 101L, 101R, 102, 103 of an axle F, R1, R2, T1, T2, Docket No.: P2022-1569 / P456436PC00 T3 on the vehicle 100. The method also comprises determining S7, by the processing circuitry, a difference ∆^, ∆^̇ in rotary motion between the first wheel rotary motion ^_^ , ^̇_^ and the second wheel rotary motion ^_^ , ^̇_^, as well as compensating S8, by the processing circuitry, the difference in rotary motion ∆^, ∆^̇ for a deviation in motion by the vehicle 100 from a straight path. The method also comprises detecting S9, by the processing circuitry, tyre explosion in case the compensated difference in rotary motion ∆^, ∆^̇ does not satisfy a second predetermined acceptance criterion. Figure 10 illustrates a computer readable medium 1010 carrying a computer program comprising program code means 1020 for performing the methods illustrated in Figure 9 and the techniques discussed herein, when said program product is run on a computer. The computer readable medium and the code means may together form a computer program product 1000. The operational steps described in any of the exemplary aspects herein are described to provide examples and discussion. The steps may be performed by hardware components, may be embodied in machine-executable instructions to cause a processor to perform the steps, or may be performed by a combination of hardware and software. Although a specific order of method steps may be shown or described, the order of the steps may differ. In addition, two or more steps may be performed concurrently or with partial concurrence. The terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" when used herein specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that, although the terms first, second, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a Docket No.: P2022-1569 / P456436PC00 second element, and, similarly, a second element could be termed a first element without departing from the scope of the present disclosure. Relative terms such as "below" or "above" or "upper" or "lower" or "horizontal" or "vertical" may be used herein to describe a relationship of one element to another element as illustrated in the Figures. It will be understood that these terms and those discussed above are intended to encompass different orientations of the device in addition to the orientation depicted in the Figures. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or intervening elements may be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. It is to be understood that the present disclosure is not limited to the aspects described above and illustrated in the drawings; rather, the skilled person will recognize that many changes and modifications may be made within the scope of the present disclosure and appended claims. In the drawings and specification, there have been disclosed aspects for purposes of illustration only and not for purposes of limitation, the scope of the inventive concepts being set forth in the following claims.

Claims

Docket No.: P2022-1569 / P456436PC00 CLAIMS 1. A computer system (130, 800) for detecting tyre explosion in a heavy-duty vehicle (100), the computer system (130, 800) comprising processing circuitry configured to: obtain control input data indicative of a control input (475) to one or more motion support devices, MSD, (430) of the heavy-duty vehicle (100), obtain a model (300) of vehicle dynamics configured to predict a motion response by the heavy- duty vehicle (100) to a control input, predict a motion response by the heavy-duty vehicle (100) to the control input (475) using the model (300) of vehicle dynamics, obtain vehicle motion data (445) from a sensor system (440) of the heavy-duty vehicle (100) indicative of an actual motion response by the heavy-duty vehicle (100) to the control input (475), and detect tyre explosion in case a difference between the predicted motion response by the heavy- duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) does not satisfy a first predetermined acceptance criterion. 2. The computer system (130, 800) according to claim 1, where the model of vehicle dynamics is any of a one-track vehicle dynamics model, a two-track vehicle dynamics model, and/or a look-up table of motion response by the heavy-duty vehicle (100) to different control inputs. 3. The computer system (130, 800) according to claim 1 or 2, where the control input comprises an applied steering angle (^). 4. The computer system (130, 800) according to any previous claim, where the model of vehicle dynamics (300) is parameterized by vehicle speed over ground (^_^). 5. The computer system (130, 800) according to any previous claim, where the model of vehicle dynamics (300) is parameterized by front and rear axle stiffness (^_^ , ^_^), vehicle wheelbase dimension (^_^ , ^_^), vehicle mass (^), and vehicle yaw inertia (^_^). Docket No.: P2022-1569 / P456436PC00 6. The computer system (130, 800) according to any previous claim, where the model of vehicle dynamics (300) has model state variables that comprise at least lateral speed (^_^) and yaw rate (^_^). 7. The computer system (130, 800) according to any previous claim, where the vehicle motion data comprises acceleration data obtained from an inertial measurement unit, IMU. 8. The computer system (130, 800) according to any previous claim, where the difference between the predicted motion response by the heavy-duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) comprises a difference in yaw rate (^_^). 9. The computer system (130, 800) according to any previous claim, where the difference between the predicted motion response by the heavy-duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) comprises a difference in lateral speed rate (^̇_^) of the front axle of the heavy-duty vehicle (100). 10. The computer system (130, 800) according to any previous claim, where the difference between the predicted motion response by the heavy-duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) comprises a difference in lateral vehicle front axle force (^_^^). 11. The computer system (130, 800) according to any previous claim, where the predetermined acceptance criterion comprises a weighting of a plurality of difference metrics. 12. The computer system (130, 800) according to any previous claim, where the weighting is determined in dependence of an operating condition of the heavy-duty vehicle (100). 13. The computer system (130, 800) according to any previous claim, where the processing circuitry if further configured to: obtain wheel rotation data indicative of a first wheel rotary motion (^_^ , ^̇_^) and of a second wheel rotary motion (^_^, ^̇_^), for first and second wheels (101L, 101R, 102, 103) of an axle (F, R1, R2, T1, T2, T3) on the vehicle (100), determine a difference (∆^, ∆^̇) in rotary motion between the first wheel rotary motion (^_^, ^̇_^) and the second wheel rotary motion (^_^ , ^̇_^), Docket No.: P2022-1569 / P456436PC00 compensate the difference in rotary motion (∆^, ∆^̇) for a deviation in motion by the vehicle (100) from a straight path, and detect tyre explosion in case the compensated difference in rotary motion (∆^, ∆^̇) does not satisfy a second predetermined acceptance criterion. 14. The computer system of claim 13, where the first wheel rotary motion (^_^, ^̇_^) and the second wheel rotary motion (^_^, ^̇_^) comprises wheel speed and/or wheel acceleration. 15. The computer system of any of claims 13-14, where the deviation in motion by the vehicle (100) from a straight path comprises any of; yaw motion (^_^) and yaw motion rate (^̇_^). 16. The computer system of any of claims 13-15, where the processing circuitry is configured to detect tyre explosion in case the difference between the predicted motion response by the heavy-duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) does not satisfy the first predetermined acceptance criterion and/or in case the compensated difference in rotary motion (∆^, ∆^̇) does not satisfy the second predetermined acceptance criterion. 17. The computer system of any previous claim, where the processing circuitry is configured to adjust motion of the heavy-duty vehicle (100) in response to detecting a tyre explosion. 18. The computer system of any previous claim, where the processing circuitry is configured to lower vehicle speed of the heavy-duty vehicle (100) in response to detecting a tyre explosion. 19. The computer system of any previous claim, where the processing circuitry is configured to adjust an admissible steering torque of the heavy-duty vehicle (100) in response to detecting a tyre explosion. 20. The computer system of any previous claim, where the processing circuitry is configured to trigger generation of a warning signal to a driver of the vehicle (100) in response to detecting a tyre explosion, and/or trigger generation of a notification message to an autonomous drive system of the vehicle (100) in response to detecting a tyre explosion. Docket No.: P2022-1569 / P456436PC00 21. The computer system of any previous claim, where the processing circuitry is configured to activate a corrective steering function and/or an oversteer guidance system of the heavy-duty vehicle (100) in response to detecting a tyre explosion. 22. The computer system of any previous claim, where the processing circuitry is configured to determine a road surface roughness, and to discard a detected tyre explosion in case the road surface roughness does not satisfy a predetermined roughness acceptance criterion. 23. A heavy-duty vehicle (100) comprising the computer system of any previous claim. 24. A computer-implemented method for detecting tyre explosion in a heavy-duty vehicle (100), the method comprising: obtaining (S1) control input data indicative of a control input (475) to one or more motion support devices, MSD, (430) of the heavy-duty vehicle (100), obtaining (S2) a model (300) of vehicle dynamics configured to predict a motion response by the heavy-duty vehicle (100) to a control input, predicting (S3) a motion response by the heavy-duty vehicle (100) to the control input (475) using the model (300) of vehicle dynamics, obtaining (S4) vehicle motion data (445) from a sensor system (440) of the heavy-duty vehicle (100) indicative of an actual motion response by the heavy-duty vehicle (100) to the control input (475), and detecting (S5) tyre explosion in case a difference between the predicted motion response by the heavy-duty vehicle (100) and the actual motion response by the heavy-duty vehicle (100) does not satisfy a first predetermined acceptance criterion. 25. The method according to claim 24, further comprising obtaining (S6), by processing circuitry of a computer system, wheel rotation data indicative of a first wheel rotary motion (^_^, ^̇_^) and of a second wheel rotary motion (^_^, ^̇_^), for first and second wheels (101L, 101R, 103) of an axle (F, R1, R2, T1, T2, T3) on the vehicle (100), determining (S7), by the processing circuitry, a difference (∆^, ∆^̇) in rotary motion between the first wheel rotary motion (^_^, ^̇_^) and the second wheel rotary motion (^_^, ^̇_^), Docket No.: P2022-1569 / P456436PC00 compensating (S8), by the processing circuitry, the difference in rotary motion (∆^, ∆^̇) for a deviation in motion by the vehicle (100) from a straight path, and detecting (S9), by the processing circuitry, tyre explosion in case the compensated difference in rotary motion (∆^, ∆^̇) does not satisfy a second predetermined acceptance criterion. 26. A computer program product comprising program code for performing, when executed by the processing circuitry, the method of claim 24 or 25. 27. A non-transitory computer-readable storage medium comprising instructions, which when executed by processing circuitry, cause the processing circuitry to perform the method of claim 24 or 25.