GB2534886A

GB2534886A - Control system

Info

Publication number: GB2534886A
Application number: GB1501778.3A
Authority: GB
Inventors: Tsampardoukas Georgios
Original assignee: Jaguar Land Rover Ltd
Current assignee: Jaguar Land Rover Ltd
Priority date: 2015-02-03
Filing date: 2015-02-03
Publication date: 2016-08-10
Anticipated expiration: 2035-02-03
Also published as: WO2016124629A1; GB201501778D0; GB2534886B; EP3253629A1

Abstract

The present disclosure relates to a control system for controlling a dynamic system of a vehicle (10 fig. 1). The control system comprises; an input 28 for receiving measured vehicle parameters in real time during a wheel slip event. The control system also comprises a controller 26 including an algorithm arranged to calculate a maximum tire-road adhesion coefficient, kmax, in real time based on the measured vehicle parameters. The controller 26 is arranged to generate a command signal arranged to configure a dynamic system of the vehicle for operation based on the adhesion coefficient, kmax. The control system also comprises an output 30 for outputting the command signal to the dynamic system of a vehicle. kmax is calculable during two or more vehicle modes, said vehicle modes including a stationary mode, a traction mode, and a braking mode.

Description

CONTROL SYSTEM

TECHNICAL FIELD

The present disclosure relates to a control system for controlling a dynamic system of a vehicle. Aspects of the disclosure relate to a controller for a dynamic system of the vehicle, a vehicle dynamic system, an electric or hybrid electric vehicle, and a method of operating a dynamic system of a vehicle.

BACKGROUND

A typical land vehicle, such as a car or the like, includes a braking system for retarding the wheels through the application of friction. The braking system includes a brake pedal, to be operated by a driver of the car, and a brake, for instance, a disc brake or a drum brake, for applying friction to a brake disc or wheel drum respectively, to retard the wheel. Typically, there is a direct mechanical link between the brake pedal and the brake such that the brakes apply friction to slow the wheels in response to depression of the brake pedal by the driver.

Some braking systems have more sophisticated operation which may include a degree of computerised control in the form of a control protocol. Typical braking control protocols control the brakes to apply differing degrees of friction or to apply an Anti-lock Braking System (ABS), depending on the degree of wheel slip currently being experienced by the wheels. For instance, if the control protocol has knowledge of the maximum wheel slip ratio and can measure the current wheel slip ratio of the vehicle, ABS can be applied in a timely fashion, immediately prior to maximum wheel slip ratio, to prevent the vehicle skidding on the driving terrain. However, understanding accurately the maximum wheel slip ratio is problematic since it is linked to the maximum tire-road adhesion coefficient, kmax, which is not directly measurable.

Typically, kmax has been estimated off-line using empirical data or theoretical calculation. The estimated kmax can then be used by the braking system in real time to determine an appropriate braking control protocol based on the degree of wheel slip. Such measures are inherently inaccurate since kmax is multi variable and depends on factors such as the current driving terrain and weather state.

Accordingly, off-line estimates of kmax do not provide accurate predictions as to when the maximum wheel slip ratio will occur in real time.

There have been attempts to calculate km, in real time based on measurable vehicle parameters so as to provide a more up to date and more accurate estimation of k,. One attempt at calculating kma" in real time can be found in a publication in "Control Theory and Applications" by the Institute of Engineering and Technology (IET) by authors M. Tanelli, L. Piroddi, and S. M. Savaresi. This IET publication describes a formula and curve fitting method for estimating kma" in real time, based on vehicle parameters measured during a braking event, when wheel slip naturally occurs. The formula is k(a; t) -(i_A(0).Fz(t).4.

co(t)r (1-A (t)) b (0-A(t) (Poi (0) The above formula is used to obtain discrete k values over the duration of the braking event. A Burckhardt model is then applied to the discrete k values and a curve of best fit constructed accordingly. The maximum value for k based on the fitted curve is then determined to be kma, Although such a method is an improvement on using an offline estimate for kmax, the method is still not ideal. For instance, the aforementioned formula is only valid during a braking event. In practice, wheel slips occur in vehicle modes other than braking, such as during a traction mode when an angular velocity of the wheel maybe too great for the terrain on which the vehicle is driving. Similarly, a wheel slip may occur when a vehicle turn radius is too excessive for the current weather conditions or terrain type, particularly when ice is present. In these cases, any control logic used to control motion of the vehicle during traction, may be using an outdated kmax value since the vehicle may be driving in different conditions to the conditions during the previous braking event.

It is an object of the present invention to address disadvantages associated with the prior art.

SUMMARY OF THE INVENTION

Aspects and embodiments of the invention provide a controller for a controller for controlling a dynamic system of a vehicle, a vehicle dynamic system, an electric or hybrid electric vehicle, and a method of controlling a dynamic system of a vehicle as claimed in the appended claims.

According to an aspect of the present invention there is provided a control system for controlling a dynamic system of the vehicle, said control system comprising; an input for receiving measured vehicle parameters in real time during a wheel slip event; a controller including an algorithm arranged to calculate a maximum tire-road adhesion coefficient, kma", in real time based on the measured vehicle parameters, and said controller arranged to generate a command signal arranged to configure a dynamic system of the vehicle for operation based on the maximum tire-road adhesion coefficient, km"; and an output for outputting the control signal to the dynamic system of the vehicle; wherein km" is calculable during two or more vehicle modes, said vehicle modes including a stationary mode, a traction mode, and a braking mode.

Operating the dynamic system based on kma", reduces the risk of uncontrollable wheel slip, e.g. skidding. Wheel slip events can occur in various vehicle modes, not just braking, and so this controller is more reliable than the prior art, since the present controller updates kma" more often. In turn, a dynamic system other than the braking system will benefit since the km" value which it uses is not based on a previous braking event, which may have occurred some time ago.

The controller may be configured to calculate km" during the braking mode using: (1 -X -) T sines-)1/4.. 1 0

krna" - -F (T, o), A, i) (1 jrA.) Fz [Cm-A) + (rni The controller may be configured to calculate kma, during the braking mode using: (0 sin oi + 1 -A kmax r Fz [(Ike) + (ii4w)1 = F, co, Ain The controller may be configured to calculate km" during the braking mode using: -k, /71-+ (. k" + Om + Beg -k,1," F," sin(6,)) + Om 0 k r1 IF,' (1-H3) sin ((It) kmax The measured vehicle parameters may be selected from the list of vehicle velocity, V, applied torque, T, wheel rotational speed, w, downwards force on a wheel, F7, steering column angle, 8,, and an electronic power assisted steering (EPAS) system motor angle, Om.. These parameters are measurable during these wheel slip events.

All of the other parameters required for calculating km" are derivable from these parameters.

The controller may be arranged to determine the maximum tire-road adhesion coefficient, km"" using differential calculus to find the maximum extrema. Determining kmax in this way is more reliable and requires less computing time than using a curve fitting method as known from the acknowledged prior art. Accordingly, the braking system will be more reliable as a result of using this technique of determining kmax.

The controller may be arranged to select between the braking, traction and stationary modes, wherein the braking mode may be selected when T is less than zero, the traction mode may be selected when T is greater than zero, and the stationary mode may be selected when T is equal to zero and when steering torque, Td, is not equal to zero. T is directly measurable and so using control logic to select between each of the formulae in this way is thought to be relatively simple, quick to compute, and reliable.

The controller may be arranged to calculate an actual tire-road adhesion coefficient, k, and wherein the command signal may be arranged to configure the dynamic system for operation based on the relationship between the maximum tire-road adhesion coefficient, km," and the actual tire-road adhesion coefficient, k. Using k and kmax is more direct than methods known from the prior art, which methods, such as the acknowledged prior art, typically extimate a k value indirectly based on a curve of best fit predicted between k and wheel slip, A. The controller may be configured to calculate the tire-road adhesion coefficient, k using: k = kmax (rx). max

This formula for determining k is simple to compute and requires less computer power than the curve fitting method known from the prior art.

The controller may comprise a verification module arranged to verify the accuracy of k by estimating an estimated average tire-road adhesion coefficient, k, using a predefined model and comparing k with k to generate a confidence signal, ice. In this way, computational errors of the controller will be detected and can thus be dealt with accordingly.

The verification module may be configured to generate k based on kmax and wheel slip ratio, A. The controller may be arranged to allow or prevent the output from outputting the control signal to the braking system depending on the magnitude of ke. A relatively small magnitude of ke will indicate that there is either no computational error from the controller or that there is some degree of error but not sufficient to warrant de-coupling the controller from the braking system. A relatively high magnitude of k, will indicate that there is sufficient computational error from the controller to warrant de-coupling the controller from the braking system. In this way, by allowing or preventing the controller from outputting the command signal, depending on the accuracy of the controller's computation, erroneous operation of the dynamic system is minimised.

The controller may be arranged to send a wheel slip request, using the output, to induce actively a wheel slip event, in real time. Inducing a wheel slip event actively allows for more frequent updates of kmax and a higher degree of control with regards to when kmax updates are obtained. This is in contrast to obtaining updates for kmax passively as and when wheel slip events occur naturally.

The controller may be arranged to send the wheel slip request to a braking system to apply a braking impulse to affect momentarily the wheel slip event. Alternatively, the controller may be arranged to send the wheel slip request to a wheel motor to apply a power impulse to a wheel of the vehicle to affect momentarily the wheel slip event.

As an another alternative, the controller may be arranged to send the wheel slip request to an electronic power steering system (EPAS) to apply a displacement impulse to a wheel of the vehicle to affect momentarily the wheel slip event. The braking impulse may be more suited to a particular vehicle mode, for instance, braking mode, where a sudden power impulse may be undesirable from a vehicle controllability point of view and a braking impulse may remain undetectable by an occupant of the vehicle. In contrast, the power impulse may be more suited to another vehicle mode, for instance, traction mode, where sudden power impulses may remain undetectable from an occupant of the vehicle where a braking impulse may be undesirable from a vehicle controllability point of view. The stationary mode may benefit from the impulse being generated from the EPAS as a displacement impulse of the wheel since a power impulse would not be suitable and the braking impulse would not yield any results due to the vehicle either being stationary or travelling at very low speeds.

Preferably, the dynamic system comprises a braking system, a wheel motor, or an electronic power assisted steering (EPAS) system.

According to a further aspect of the present invention, there is provided, a vehicle dynamic system comprising the aforementioned controller.

According to a further aspect of the present invention, there is provided an electric or hybrid electric vehicle comprising the aforementioned dynamic system.

According to a further aspect of the present invention, there is provided a method of controlling a dynamic system of a vehicle, the method comprising; receiving vehicle parameters in real time during a wheel slip event; calculating a maximum tire-road adhesion coefficient, kiwi, in real time based on the measured vehicle parameters; generating a command signal arranged to configure a dynamic system of the vehicle for operation based on k,", and outputting the command signal to the dynamic system; wherein kma" is calculated during two or more vehicle modes, said vehicle modes including a stationary mode, a traction mode, and a braking mode.

The method may comprise calculating k, during braking mode using: (1 X\ k JO) T sines-A - , kmax (1) rX) Ez [Cf'-4 A.) (r2)] F (T co, A, The method may comprise calculating k,during traction mode using: (r)2 T sin co + 1-CO kmax r F, [GIL) + (iwrV2)] = F, co, A, A.) The method may comprise calculating kmaxduring stationary mode using: -ke + + wr) ea, + Beg -IctIm + Fil, sin(6m) + Jeg en, 0 (k. krR2r, IF,I (1 -H3) s (um The method of calculating km," may use vehicle parameters selected from the list of vehicle velocity, V, applied torque, T, wheel rotational speed, w, downwards force on a wheel, Fr, steering column angle, Oa, and an electronic power assisted steering (EPAS) system motor angle, 0",.

The method may comprise differentiating the or each aforementioned equation and obtaining the maximum extrema to determine kma".

The method may comprise selecting between the braking, traction and stationary modes, preferably selecting the braking mode when T is less than zero, preferably selecting the traction mode when T is greater than zero, and preferably selecting the stationary mode when T is equal to zero.

The method may comprise calculating a tire-road adhesion coefficient, k, in real time and configuring the dynamic system to operate based on the relationship between the maximum tire-road adhesion coefficient, kmax and the tire-road adhesion coefficient, k.

The method may comprise calculating the tire-road adhesion coefficient, k, using: k = kmax (-) Ana" kmax -The method may comprise verifying the accuracy of k by estimating an estimated average tire-road adhesion coefficient, k, using a predefined model and comparing k with k to generate a confidence signal Ice.

Preferably, verifying the accuracy of k is achieved by using kma, and wheel slip ratio, A, as inputs to the predefined model to generate R. The method may comprise allowing or preventing output of the command signal to the dynamic system depending on the magnitude of ke.

The method may comprise sending a wheel slip request to induce actively a wheel slip event, in real time.

The method may comprise sending the wheel slip request to a braking to apply a braking impulse to affect momentarily the wheel slip event. Alternatively, the method may comprise sending the wheel slip to a wheel motor to apply a power impulse to a wheel of the vehicle to affect momentarily the wheel slip event. In contrast, the method may comprise sending the wheel slip request to an electronic power steering system (EPAS) to apply a displacement impulse to a wheel of the vehicle to affect momentarily the wheel slip event.

The dynamic system may comprise a braking system, a wheel motor, or an EPAS system.

Within the scope of this application it is expressly intended that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and/or in the following description and drawings, and in particular the individual features thereof, may be taken Independently or in any combination. That is, all embodiments and/or features of any embodiment can be combined in any way and/or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and/or incorporate any feature of any other claim although not originally claimed in that manner.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure 1 shows a schematic view of an electric vehicle including a controller according to an embodiment of the present invention; Figure 2 shows a free body diagram of a wheel from the vehicle shown in Figure 1; Figure 3 shows an electronic power assisted steering (EPAS) system of the vehicle from Figure 1; Figure 4 shows a block diagram of the controller from the vehicle shown in Figure 1; Figure 5 shows a block diagram of further aspects of the controller from Figure 1; Figure 6 shows verification test data for the controller operating in a braking mode with a anti-lock braking system (ABS) on; Figure 7 shows verification test data for the controller operating in a braking mode and displaying braking torque and wheel slip against tire-road adhesion coefficient; Figure 8 shows verification test data for the controller operating in a braking mode and displaying tire-road adhesion coefficient against wheel slip; Figure 9 shows verification test data for the controller operating in a braking mode with ABS off; Figure 10 shows a similar view to Figure 6 of a different verification test with ABS on; 20 and Figure 11 shows a similar view to Figure 9 of the same verification test as Figure 10 but with ABS off.

DETAILED DESCRIPTION

With reference to Figure 1, an electric (or hybrid electric) land vehicle 10, such as a car, includes various dynamic systems for controlling its motion. These dynamic systems include a traction system, a braking system, and an electronic power steering (EPAS) system.

The vehicle 10, includes a vehicle body 12 for supporting a battery 14 and four wheels 16. The wheels 16 are supported by respective side shafts 18. At least two of the wheels 16 are driven wheels in that power is supplied to them by the traction system to move the vehicle 10. The traction system includes wheel motors 20 for powering the wheels by rotating the side shafts 18 connected to the driven wheels 16. In this case, the vehicle 10 is a rear wheel drive vehicle since only the rear wheels 16 are connected to respective wheel motors 20. Power to the wheel motors 20 is supplied by the battery which is rechargeable from a power grid. In the case of a hybrid electric vehicle, a generator 22 may be incorporated to recharge the battery for periods when the vehicle is operating in an electric mode.

The braking system includes two or more brakes 24, each brake for retarding one of the wheels. In this case, there are two brakes 24, each for retarding a front wheel 16.

The brakes 24 are disc brakes and operate in response to a driver depressing a brake pedal within a cabin of the vehicle 10. Retardation of the wheels 16 is achieved by opposing brake pads compressing against a brake disc, which brake disc is fixed on the side shaft 18. A brake caliper supports and moves the opposing brake pads towards the brake disc in response to receiving a braking command signal, which will be described in further detail below. An Anti-lock Braking System (ABS) is also incorporated into the braking system which operates by application and release of the brake pads according to a predefined frequency.

The braking system is controlled according to a braking control protocol. The braking control protocol controls the braking system to apply varying degrees of braking torque, Tb, and/or induces operation of the ABS, depending on a command signal received from a control system of the vehicle 10.

The control system includes a controller 26, an input 28 and an output 30. The controller 26 and its operation are described in more detail below. The input 28 is connected to various sensors and detectors 32 provided throughout the vehicle 10, which sensors and detectors 32 measure various vehicle parameters used by the controller to generate the command signal.

For purposes of this disclosure, it is to be understood that the controller 26 described herein may comprise a control unit or computational device having one or more electronic processors. Vehicle 10 and/or a system thereof may comprise a single control unit or electronic controller or alternatively different functions of the controller may be embodied in, or hosted in, different control units or controllers. As used herein, the term "controller" will be understood to include both a single control unit or controller and a plurality of control units or controllers collectively operating to provide the required control functionality. A set of instructions could be provided which, when executed, cause said controller(s) or control unit(s) to implement the control techniques described herein (including the method(s) described below). The set of instructions may be embedded in one or more electronic processors, or alternatively, the set of instructions could be provided as software to be executed by one or more electronic processor(s). For example, a first controller may be implemented in software run on one or more electronic processors, and one or more other controllers may also be implemented in software run on or more electronic processors, optionally the same one or more processors as the first controller. It will be appreciated, however, that other arrangements are also useful, and therefore, the present invention is not intended to be limited to any particular arrangement. In any event, the set of instructions described above may be embedded in a computer-readable storage medium (e.g., a non-transitory storage medium) that may comprise any mechanism for storing information in a form readable by a machine or electronic processors/computational device, including, without limitation: a magnetic storage medium (e.g., floppy diskette); optical storage medium (e.g., CD-ROM); magneto optical storage medium; read only memory (ROM); random access memory (RAM); erasable programmable memory (e.g., EPROM ad EEPROM); flash memory; or electrical or other types of medium for storing such information/instructions.

With reference to Figure 2, a wheel 16 is shown together with vehicle parameters continuously monitored by the input 28 (Figure 1). Details of the wheel 16 are not shown though the outer periphery of the wheel includes a tire 17.

With reference to Figure 3, the EPAS system 36 includes a steering wheel 38, a steering column 40, a motor 42, a gear arrangement 44, and a track rod 46 for turning the wheels 16. The EPAS also include a rack and pinion arrangement 48 for converting rotational movement from the steering column 40 into linear motion of the track rod 46. Various vehicle parameters, measured on the EPAS 36, are continuously monitored by the input 28 (Figure 1). The EPAS 36 works by the driver turning the steering wheel 38 and, in response, the motor rotates the pinion, via the steering column 40 to turn the wheels 16 via the track rod 46.

The measured vehicle parameters include vehicle velocity, V, angular velocity of the wheel, w, applied torque T (torque of the wheel motor 20), downwards force on a wheel, F, (which is an estimated parameter based on a mass calculation of the vehicle), steering column angle, Q, and EPAS system motor angle, O. However, as can be seen from the various equations below, not all of the aforementioned vehicle parameters are required for calculating a km," value during each mode. For instance, calculating icy-flax during the traction and braking modes does not require inputs for 0, and Om.

The controller 26 (Figure 1) is arranged to operate in three vehicle modes, namely a "braking mode", a "traction mode", and a stationary or very low speed mode which hereinafter is termed a "stationary mode". A wheel slip event can occur in any of these modes. Each mode uses a unique set of equations to determine the command signal to be sent to the dynamic systems. These equations are provided on an algorithm of the controller 26. These equations are dealt with in turn below, however, the braking and traction modes are based upon those parameters referenced in Figure 2. In contrast, equations governing the stationary mode are based on those parameters referenced in Figure 3. The controller decides which set of equations to process based on the current value of applied torque, T, and steering wheel torque, Td. When T is less than zero, the equations relating to braking mode are processed. When T is equal to zero, the equations relating to traction mode are processed. Finally, when T is equal to zero, and when Td is not equal to zero, the equations relating to stationary mode are processed.

Although the actual equations governing each mode are different, the aim is the same. For instance, each equation generates a value for the maximum tire-road adhesion coefficient, k","", in real time based on the measured parameters relating to the identified vehicle mode. Using k","," the algorithm determines a current value of the tire-road adhesion coefficient, It The formula used in calculating k will be described in further detail below. However, in summary, k is compared to km," and a command signal is sent, by the output 28 of the controller 26, to one of the dynamic systems to operate based on the relationship between k and kma", so that the risk of uncontrollable wheel slip in traction, braking, and stationary modes is minimised. The dynamic system may be any system effecting the motion of the vehicle 10. As defined above, dynamic systems include the braking system, the wheel motors 20 (Figure 1) and the EPAS system 36.

The construction of the algorithm is best described by detailing each vehicle mode in turn below. Each of the subsequently identified modes should be read in conjunction with Figure 4, which shows a block diagram of the controller 26 in operation. In brief, the controller 26 in operation includes the input 28 and the output 30. The input 28 communicates with the algorithms 50 for determining k",". A correcting factor 52 for calculating k, is also communicative with the algorithms 50. The input 28 is also in communication with a trigger logic function 54. The trigger logic function is a rule based, decision making logic, which uses existing measurements to define when and which wheel has experienced an unexpected wheel slip event. Based on this information, and with knowledge of the vehicle mode (e.g. driving mode, braking mode, or stationary mode), the trigger logic will be able to decide when and how the electric motors of the wheels 16 will be controlled. For instance, when the vehicle measures a high level of wheel acceleration or a high level of change of the rate of wheel acceleration, then the decision making logic will be able to decide the impulse test (e.g. power impulse magnitude or braking impulse magnitude) required to induce actively the wheel slip event to generate actively a kmax value.

Outputs from the algorithm 50 and the trigger logic 54, namely km" and Amax, and a trigger value respectively, are input to a data store 56 of the controller 26 for future reference. The most recently recorded values in the data store 56 are used by the controller 26, together with a current value for k, to generate the command signal.

Braking Mode With further reference to Figures 2 and 4, a free body diagram of a wheel 16 and all the forces and torques applied to the wheel 16, during a braking event, are shown. An itemised list of the parameters shown in Figure 2, together with those derived from equations (1) to (4) below, is provided below equation (3). At this stage only a static element of the vertical load of the tire is used, neglecting any weight transfer.

The weight transfer element will be added in future developments and optimisations.

Additionally, the wheel inertia and the wheel radius assumed to be constant at all time.

J cb = r Fx -T sign (w) (1) mV = -Fx (2) Fx = kmaxFz (3) where co is the angular speed of the wheel 16 in rad/s, V is the longitudinal speed over ground in m/s, T is the braking torque in Nm, Fr is the longitudinal tire-road contact force in N, J is the moment of inertial of the wheel in Kgm2, m is the single mass corner in Kg and r is the wheel radius in m.

The wheel slip ratio, during braking mode, is defined as V -cor

-

max(V,e) (4) where e is a constant of very small value to avoid zero denominator. The nominal value of e = 0.001 is used in this paper.

Differentiating equation (4) and substituting (1), (2) and (3), produces a new non-linear equation: (1 r2 wr [F, kmax (5) +T sin w J con Rearranging (5) for tire-road adhesion coefficient, k, a new mathematical equation for peak tire-road adhesion coefficient, k",,, is obtained, during braking: kmax (11ZA) T sin w - -F (T, m, X, X) (6) 1 -X ct) Ex Ki 1±1 ± (14)1 Equation (6) is a highly non-linear function that correlates the brake torque and the wheel slip ratio, the rate of change of slip in one equation that calculates the peak tire-road adhesion coefficient, kma", during braking in real time. This equation is also highly prone to noisy signals of wheel slip measurements so extra care needs to be taken in order to acquire robust data.

Traction mode Still with reference to Figures 2 and 4, the equations of motion that govern the system during traction mode are: J m = -r Fx T sign (w) (7) mV = Fx (8) where T is the traction force delivered to the wheel 16. Additionally, the wheel slip ratio in traction mode is defined as con -V max(wr,e) (9) Differentiating (9) and substituting (7), (8) and (3), a new equation is derived: 1= (1 -X r2 (1 - r 1 -X cor) [F M (J) ( cur) T sin co (10) Rearranging (10) for tire-road adhesion coefficient, k, a new non-linear equation is obtained for traction mode: (D2 T sin + 1 -A r F, [(w+0) + (jrv4)1 = F (T, w, A, A) Stationary Mode With reference to Figures 3 and 4, a model based approach is selected to encapsulate the concept of calculating in real time the tire-road adhesion coefficient, k, during the stationary mode. The entire concept is based on the assumption that at very low vehicle speed, or whilst the vehicle is stationary, in a longitudinal mode, the driver will provide some amount of steering in order to get enough slip to estimate the peak tire-road adhesion coefficient, kma". This is the initial value of the peak tire-road adhesion coefficient, kmax, and as the vehicle braking and accelerating, corrective action will occur. The entire philosophy is based on the assumption that the best educated estimate for the peak adhesion can be provided only at the time that the steering input is equal to tire self-alignment torque. Systematic and random error should be taken into account due to model imperfections and measurement noise, respectively. It is also assumed that this method of calculating the maximum tire-road adhesion coefficient, kmax, is suitable only for the stationary or very low vehicle speeds in longitudinal mode because all calculations have been made on the quasi-static region of the vehicle dynamic behaviour, avoiding vehicle dynamic elements such as side slip, tire slip angle and so on.

EPAS and a simple tire model are used to develop the algorithm in a stationary mode. One such tire model is known as the Fiala tire model and is obtained using equations (16) and (17) below. The Fiala tire model is a very simple model to introduce the principle of the entire concept. More complicated tire models (e.g. a Magic formula model) could be potentially incorporated to enhance the accuracy and robustness of the algorithm. The dynamic analysis of the EPAS and the motor characteristics are described in more detail below.

With reference to Figure 3, the EPAS free body diagram is shown with all the torques applied into the system. Dynamic equations (12) to (15) below, describe a linearized version of the system. The parameters referenced in equations (12) to (15) are itemised below equation (15).

J, = -K,O, -B, 6, + K, 141 -F, sign (0,) + Td k krfq, Jeq Om = kc ± N2) ein -Beg em ktim -Fn, sin(0") -TL L., Im = -Rmlm-KO), + U Td = k, (13, -11) NKtl," Tt where, J, is the steering column moment of inertia, IQ is the steering column stiffness, B, is the steering column viscous damping, 6, is the steering wheel angle, 6mis motor angle, N is motor gear ratio, F, is the steering column friction, Jepis the equivalent inertia, kr is the tire spring rate, Rp is the steering column pinion radius, kt is the motor torque, constant voltage, Imis the motor current, Fmis the motor friction, U is motor terminal voltage, Lin is motor inductance, Rm is the motor resistance and Tt is the tire reaction force.

The simple Fiala tire model is obtained by the equations (16)-(17) and equation (18) describes that the steering angle, 0,, is a linear function of the motor angle, 0m.

Mz = -k IFz I (1 -Ha) s H -1 (Caltan(5)r\ 3 k Fz) Urn where M,is the self-aligning torque of the tire, Ca is the cornering stiffness and 8 is the steering angle. (12) (13) (14) (15) (5)

These equations are valid when using various assumptions. For instance, when a driver is applying steering torque, when the vehicle is moving in longitudinal mode with very low speed and neglecting all mechanical and electrical losses, then the steering angle is equal to self-alignment torque of the tire Tt = M. This assumption is only true under specific conditions. Rearranging (13) for M, and substituting (12) and (14) -(18) to (13), then a new non-linear equation is derived as shown in (19) to describe the adhesion coefficient in this mode. k= 7

(, k,R2, -k, + 7+ °,1,+ Beg 6m -ktlmFm sin(Bo,) + Je iFz I (1 -H3) sin 41) /R2 /122 \ where B = B),)B and leg Jrn + K-eg m N2 r N2 As described above, the controller is able to execute the equations relating to each mode in response to detecting which mode the vehicle is current operating in. This is done by monitoring the values of applied torque, T, and steering wheel torque, Td, in real time. Having knowledge of the applied torque, the controller 26 executes the corresponding equations relating to that mode as shown in equation (20) below.

One unified equation is generated to represent the peak adhesion coefficient, kmax, algorithm for three different vehicle modes, as shown in (20). Maximum tire-road adhesion coefficient, kmax, is determined by differentiating each equation for, k, and finding the maximum extrema.

kmax r)2 T sin co (7) +1 -A G410) rwV2 Fo.

k, 114+ +42a) en, + Beg ern ktli, + Fm sin(0")) + ieq ern IFz1 -1-1') sin rtr) (÷A) T sin co -1 -A ) F2 [(11±1A) (4)] T > 0 (Traction Mode) (20) T = 0 and Td t 0 (Stationary) T < 0 (Braking Mode) (19) Because this algorithm stands only at the peak of the adhesion curve, a corrective action is required to reduce the value of the adhesion coefficient, as introduced in equation (21).

k = kma" (21) nmax The command signal sent to one of the dynamic systems is based on the relationship between k and lc-flax. For instance, the command signal may be sent to any of the EPAS 36, the braking system, and a wheel motor 20 to operate based on k and kma" so as to prevent uncontrollable wheel slip occurring. Such a range of usage of the controller is not possible using any of the known algorithms of the prior art, which are limited to single mode usage.

It is important to note that the aforementioned equations require wheel slip events to occur in order to generate values for the constituent vehicle parameters. Such wheel slip events occur naturally, for instance during a braking event. However, it is also possible to affect actively a wheel slip event in a few ways. For instance, a braking impulse could be sent from the controller 26 to the braking system to apply maximum braking force for an instantaneous time period. This braking impulse will instantaneously generate a wheel slip event which in turn will generate numerical values for the constituent parameters of the aforementioned equations relating to braking and tractions modes. Alternatively, it is possible to affect actively a wheel slip event by applying a power impulse to one or more of the driven wheels 16 using the motors 20 (Figure 1). The impulse is instantaneous and should cause a momentary wheel slip event for the generation of numerical values for the aforementioned equations for braking and traction modes. Regardless as to the type of wheel slip request, i.e. either a braking impulse or a power impulse, the wheel slip event should remain largely undetectable for vehicle occupants due to them being for such a short period of time.

Braking and power impulse though are probably not particularly well suited to the stationary mode. Accordingly, the wheel slip event is determined by a displacement impulse by the EPAS motor moving the track rod over an angle which is sufficient to cause a wheel slip event but which is insufficient to be detectable by a vehicle occupant. In this way, the controller 26 is able to affect actively a wheel slip event in all three vehicle modes.

With reference to Figure 5, the controller 26 also includes a verification module 60 for verifying the accuracy of the algorithms 50. The verification module 60 uses a predefined model 62, which model is an inverse tire model. Inputs to the inverse tire model are A and kme,e where A is also an input to the tire-road adhesion coefficient algorithms 50 and where k" is an output from the algorithms 50. The inverse tire model determines an estimated average tire-road adhesion coefficient, cc, which is used as a comparator against the calculated tire-road adhesion coefficient, k, output from the corrective formula (formula (21) described above). In particular, k, is subtracted from k, to produce an error signal, ke. The controller uses ke to understand the accuracy of the algorithms 50. For instance, a high magnitude of ke results from an inaccurate algorithm 50. In contrast, a low magnitude of ke is either due to an inaccurate algorithm 50 or both an inaccurate inverse tire model and an inaccurate algorithm 50. However, the inverse tire model is constructed so that errors in both the algorithm 50 and the inverse tire model 62, which result in the same errors in k and ke, are unlikely to occur.

The controller 26 is arranged to use the error signal, ke, to allow or prevent the output from sending the command signal to the braking system. Specifically, a high magnitude of ke is associated with an erroneous algorithm 50, so the command signal based on calculated k and k" is likely to be erroneous too. It is important to 'de-couple' the algorithm 50 in such cases since such errors may result in erroneous operation of the dynamic system.

Fidelity of the controller during the aforementioned braking mode has been verified through tests. The results of those tests are included below for reference purposes.

Braking Mode Fidelity Test Results This section evaluates the experimental results obtained from an experimental vehicle on a constraint environment (i.e. test track). Environmental and vehicle data are omitted for confidentiality reasons. The vehicle has been tested on a very low adhesion surface in a test track. The wheel slip event during braking deliberately remained on a longitudinal orientation to avoid any side slip complications and high side acceleration values. There are two different sets of results on medium and low surface roughness and with and without ABS enabled.

Figure 6 present a brake event with enabled ABS in wet road surface. The duration of brake event is about 1 second and the vehicle is decelerated from 20m/s to almost Om/s (2g deceleration). The algorithm is able to calculate the peak tire-road adhesion coefficient in real time as shown in Figure 6. The peak value of tire-road adhesion coefficient (i.e. 0.35) is calculated at about 10% of slip after 2.3ms of braking event. Additionally, the maximum slip observed after 0.5ms after the initial brake application, where the slip ratio is about 30% and the value of the tire-road adhesion coefficient at this point is around 0.13. Thus, the pattern of data extracted from Figure 6 validates that the vehicle were tested on a wet road and the maximum slip allowance is 10% to achieve the peak tire-road adhesion coefficient.

Figures 7 and 8 show the distribution of adhesion coefficient relative parameters such as brake torque and wheel slip.

Moreover, the same vehicle has been tested on the same surface under the same conditions, but the braking deceleration reduced from 2g to 1.4g as shown in Figure 9. The ABS was not enabled for the test resulting in Figure 9 and thus the maximum adhesion utilisation in this case is not achieved. The wheel slip pattern remained in the region of 5% while the maximum tire-road adhesion coefficient is calculated as much less than 0.2 (i.e.0.17). This means that the vehicle under utilises the maximum grip and there is more grip available under these conditions.

Hence, the algorithm is able to identify the tire-road adhesion coefficient in real time and to evaluate an extra available grip during the event and thus to readjust the braking actuation control protocol.

A third experiment (2.8g deceleration) has been conducted in a higher grip surface, namely a gravel road with estimated peek adhesion of 0.38. Figure 10 shows that the wheel is almost completely locked, having a slip ratio of 85% after 0.5ms and the tire-road adhesion coefficient has a very low value or approximately 0.1. In contrast, when the wheel slip ratio is 5%, the peak tire-road adhesion coefficient is 0.4.

Wither reference to Figure 11, performing again the third experiment but reducing the braking deceleration, similar results were obtained as in the second experiment.

Similarly, the adhesion utilisation is underused which means that there is much more grip available for optimum braking.

Claims

CLAIMS1. A control system for controlling a dynamic system of a vehicle, said control system comprising; an input for receiving measured vehicle parameters in real time during a wheel slip event; a controller including an algorithm arranged to calculate a maximum tire-road adhesion coefficient, km,", in real time based on the measured vehicle parameters, and said controller arranged to generate a command signal arranged to configure a dynamic system of the vehicle for operation based on the maximum tire-road adhesion coefficient, k,; and an output for outputting the command signal to the dynamic system of a vehicle; wherein kmax is calculable during two or more vehicle modes, said vehicle modes including a stationary mode, a traction mode, and a braking mode.
2. The control system of Claim 1 wherein the controller is configured to calculate kma" during the braking mode using T sin ril -kmax = j = F (T, (1,-"A-) F2R1 Ni-A)H-CIA
3. The control system of Claim 1 or Claim 2 wherein the controller is configured to calculate kma" during the traction mode using (2 9 T sin w + 1 -A kmax r Ez m1w) GrwV)1 = F (T, a), 2, j)
4. The control system of any preceding claim wherein the controller is configured to calculate k, during the stationary mode using -k,0. + + k + Beg -k,17," Fmsin(A(o) + 0,, (k. *R, IF, I(1-H3) sin () kmax
5. The control system of any preceding claim wherein the measured vehicle parameters are selected from the list of vehicle velocity, V, applied torque, T, wheel rotational speed, w, downwards force on a wheel, F,, steering column angle, Q, and an electronic power assisted steering (EPAS) system motor angle, O.
6. The control system of Claims 2, 3 or 4 wherein the controller is arranged to determine kma, using differential calculus to find the maximum extrema.
7. The control system of Claims 2, 3, and 4 or Claim 6 wherein the controller is arranged to select between the braking, traction and stationary modes, wherein the braking mode is selected when T is less than zero, the traction mode is selected when T is greater than zero, and the stationary mode is selected when T is equal to zero and when steering wheel torque, Td is not equal to zero.
8. The control system of any preceding claim wherein the controller is arranged to calculate an actual tire-road adhesion coefficient, k, and wherein the command signal is arranged to configure the dynamic system for operation based on the relationship between the maximum tire-road adhesion coefficient, km," and the actual tire-road adhesion coefficient, k
9. The control system of Claim 8 wherein the controller is configured to calculate k using k = kmax Am,
10. The control system of any preceding claim wherein the controller comprises a verification module arranged to verify the accuracy of k by estimating an estimated average tire-road adhesion coefficient, k, using a predefined model and comparing k with k to generate a confidence signal k0.
11. The control system of Claim 10 wherein the verification module is configured to generate R based on kmax and wheel slip ratio, A.
12. The control system of Claim 10 or Claim 11 wherein the controller is arranged to allow or prevent the output from outputting the control signal to the dynamic system depending on the magnitude of ke.
13. The control system of any preceding claim wherein the controller is arranged to send a wheel slip request, using the output, to induce actively a wheel slip event, in real time.
14. The control system of Claim 13 wherein the controller is arranged to send the wheel slip request to a braking system to apply a braking impulse to affect momentarily the wheel slip event.
15. The control system of Claim 13 or Claim 14 wherein the controller is arranged to send the wheel slip request to motor to apply a power impulse to a wheel of the vehicle to affect momentarily the wheel slip event.
16. The control system of any of Claims 13 to 15 the controller is arranged to send the wheel slip request to an electronic power assisted steering system (EPAS) to apply a displacement impulse to a wheel of the vehicle to affect a momentarily the wheel slip event.
17. The control system of any preceding claim wherein the dynamic system comprises a braking system, a wheel motor, or an electronic power assisted steering (EPAS) system.
18. A dynamic system of a vehicle comprising the control system of any preceding claim.
19. An electric or hybrid electric vehicle comprising the dynamic system of Claim 16.
20. A method of controlling a vehicle dynamic system, the method comprising; receiving vehicle parameters in real time during a wheel slip event; calculating a maximum tire-road adhesion coefficient, kmax, in real time based on the measured vehicle parameters; generating a command signal arranged to configure a dynamic system of the vehicle for operation based on kmax; and outputting the command signal to the dynamic system; wherein km x is calculated during two or more vehicle modes, said vehicle modes including a stationary mode, a traction mode, and a braking mode.
21. A control system for a dynamic system of a vehicle, a vehicle dynamic system, an electric of hybrid electric vehicle, or a method of controlling a dynamic system of a vehicle as substantially herein with reference to the accompanying Figures.