WO2024134484A1

WO2024134484A1 - A method for the improved management of an automotive battery, with monitoring of the energy expenditure

Info

Publication number: WO2024134484A1
Application number: PCT/IB2023/062925
Authority: WO
Inventors: Roberto Bursi; Carmine ESPOSITO; Ludovic Gaudichon
Original assignee: Maserati S.P.A.
Priority date: 2022-12-20
Filing date: 2023-12-19
Publication date: 2024-06-27

Abstract

Disclosed herein is a method for improved management of an automotive battery with the monitoring of energy expenditure (L) of an automotive battery, which enables preventing phenomena of early performance degradation (SOH) of the battery while ensuring the perception of constant performance by the user, oorr vice versa, if necessary, wwhhiillee enabling the user, by means of communications, to be aware of the impact of his driving style on the long-term useful life of the system. The method takes into account, i.a., the current operating conditions of the battery.

Description

"A method for the improved management of an automotive battery, with monitoring of the energy expenditure"

★ ★ ★ ★

TEXT OF THE DESCRIPTION

Field of the Invention

The present invention refers to at least partly electrically powered drivetrain systems , including both exclusively electric vehicles (BEVs ) and the vehicles equipped with a hybrid powertrain in the various versions thereof ( PHEVs , MHEVs , HEVs , etc . ) .

Known Art

Designing an automotive battery is currently carried out on the basis of very general guidelines , the primary purpose whereof is to guarantee a safety margin which exceeds the regulatory requirements . In other words , the si zing of an automotive battery ( obviously also including a set of batteries ) is designed with the only purpose of exceeding the target values as regards , for example , CO2 emissions , mileage , delivery of energy to the network on board the vehicle , etc .

In practice, it may be stated that the criterion for automotive battery si zing currently consists in providing one or more predicted use profiles of the batteries ; such profiles are adapted to cover the operations required from the battery by a very large margin, primarily because there is no compensation system which may act when the real operating conditions of the batteries , during real operation on board the vehicle , may lead to exceed the initial assumptions , including a user' s driving style .

More specifically, referring to Figure 1 , the si zing is currently based on maps of the type SOH ( State of Health) over mileage ( in kilometres or miles ; alternatively, the mileage may be considered in terms of an evolution in time , and in this case the X-axis will have the parameter "time" ) . Such parameters define a limit curve representing a condition ( ageing, SOH) threshold of the battery below which the target of end- of-li fe ageing ( i . e . , ageing after a reference mileage ) SOH_EOL cannot be met . Above the limit curve LSOH, on the contrary, meeting the target SOH_EOL is ensured .

The problem in the use of SOH-mileage or SOH-time maps is so to say the lack of sensitivity of such an ageing mapping to variations occurring during short drives . In other words , the ageing mapping by means of a SOH-mileage plan may permit the implementation of corrections only over long drives , during which a large part of a possible damage to the battery due to the real operating conditions - such as e . g . , the user' s driving style - remains undetected and uncontrolled .

The consequence thereof is a definitely excessive oversi zing of the batteries or, vice versa, battery mal functions i f the initial assumptions reveal to be insuf ficient , therefore failing to meet the SOH_EOL target .

Obj ect of the Invention

The invention aims at solving the technical problems outlined in the foregoing . Speci fically, the invention aims at managing the ageing of an automotive battery of a vehicle by taking into account the real operating conditions , including the user' s driving style .

Summary of the Invention

The obj ect of the invention is achieved by means of a method having the features set forth in the claims that follow, which form an integral part of the technical disclosure provided herein in relation to the invention .

Brief Description of the Figures

The invention will now be described with reference to the annexed Figures , which are provided by way of non-limiting example only and wherein :

- Figure 1 , already described in the foregoing, shows an ageing diagram of an automotive battery, as used in known methods ;

- Figure 2 shows a correspondence between the ageing diagram of Figure 1 ( Figure 2A) and an ageing diagram of an automotive battery as used in a method according to the invention,

- Figure 3 corresponds to a trans fer, onto the diagram of Figure 2B, of features of the method according to the invention, and

- Figure 4 is a block diagram representing a method according to the invention and the interaction thereof with a vehicle .

Detailed Description

Referring to Figures 2A and 2B, a premise to the method according to the invention is derived from the discussion of the known art provided in the foregoing .

Referring to Figure 2A, there is shown a conventional SOHe ( State of Health of energy) - time ( the mileage parameter , with respect to the SOHe , is replaced by a time coordinate ) plot , with the corresponding limit curve LC and the value of end-of- li fe SOHe , EOL_SOHe . The diagram also shows degradation levels i, n , ‘I’EOL respectively at the time instants 1 , n and EOL ( end of li fe ) . As discussed in the foregoing, the degradation levels dii, n, ‘I’EOL - i . e . , the decrease levels of the SOHe value - are not adapted to be used as a control variable , especially in the case of a realtime control , or anyway a control based on very shortlasting, even instantaneous , events . As a result , in the assumption of map as depicted in Figure 2A, a control based on the variables i, n, ‘I’EOL does not enable reacting to instantaneous or short-lasting events , which have a remarkable impact on the battery degradation . In this regard, the inventors have observed that the transition to a map such as that as depicted in Figure 2B better lends itself to the control needs aimed at protecting the battery from accelerated degradation phenomena. The map as depicted in Figure 2B is specifically an energy expenditure (AE) - time map, i.e. energy expenditure vs. a parameter which describes the battery useful life (time, or alternatively mileage) .

The energy expenditure parameter exhibits dynamics equal or anyway similar to the evolution dynamics of the operating conditions which the battery is subjected to, and therefore it is a parameter which is influenced, i.a., by the current driving conditions and by the boundary conditions which characterise the vehicle run.

The diagram in Figure 2B specifically shows a curve L representing the evolution of the current energy expenditure of the battery along the useful life thereof, predictions of maximum allowed total energy expenditure at the end of useful life AEi, AE_n for the operating conditions of LI and Ln at instants 1 and n of the useful life interval, and the related amounts of (cumulative) current energy expenditure Ei, t>E_n, C>EEOL at instants 1, n and end of life (EOL) .

With these assumptions, and referring to Figures 3 and 4, according to the invention there is defined a method for managing the energy expenditure of an automotive battery, including: defining an (initial) maximum allowed total energy expenditure AEo of the battery for a battery useful life interval, defining a (cumulative) limit allowed energy expenditure profile EMAX developing over the useful life interval, the cumulative limit energy expenditure E X being increasing (also at a non-constant rate, and depending on the physical characteristics of the system) up to the value of the maximum allowed total energy expenditure AEo of the battery,

- defining a target energy expenditure profile ETG ( at the beginning of useful life ) developing over the useful li fe interval , the target energy expenditure E G being increasing up to the value of the maximum allowed total energy expenditure AEo of the battery, and defining a target energy expenditure gradient ( at the beginning of useful li fe ) GRAD_E G over the useful li fe interval , which is preferably defined in spatial terms ( i . e . , mileage in km or mi ) ,

- monitoring a current energy expenditure L of the battery during the useful li fe interval , the current energy expenditure L defining a current energy expenditure gradient GRAD_L, preferably a spatial gradient based on the mileage , and even more preferably based, in addition, on an analysis of past driving data, and subsequent prediction of probable future driving,

- comparing the current energy expenditure L at an instant of useful li fe with the target energy expenditure E G at the same instant of the useful li fe , and/or comparing the current energy expenditure gradient GRAD_L at an instant of the useful li fe with the target energy expenditure gradient GRAD_ETG at the same instant of useful li fe ,

- i f a di f ference between the target energy expenditure and the current energy expenditure L is less than a first threshold value , and/or i f a di f ference between the target energy expenditure gradient GRAD_ETG and the current energy expenditure gradient GRAD_L is less than a second threshold value , respectively controlling a limitation of the current energy expenditure L and/or a limitation of the current energy expenditure gradient GRAD_L, and i f necessary controlling the issue of a warning to the driver, so as to make him aware of the ef fect of his driving style on the useful li fe of the battery .

By way of example , in Figure 3 the limit allowed energy expenditure profile EMAX is represented as a segmented curve , but it can have the shape of any continuous curve , so it must not necessarily be segmented .

Similarly, the target energy expenditure profile E G is represented as a straight line , because this is advantageous for obtaining a perception of uni form performance by the driver during the battery useful li fe ; however, it is also possible to have any curved shape - as a function of the speci fic needs - provided that it is a monotonic increasing curve and provided it ends in ( initial or updated) AEo .

Optionally, the method may preferably comprise permitting an increase in current energy expenditure L, and/or an increase in current energy expenditure gradient GRAD_L i f , respectively, a di f ference between the target energy expenditure and the current energy expenditure L is greater than a third threshold value , and/or i f a di f ference between the target energy expenditure gradient GRAD_ETG and the current energy expenditure gradient GRAD_L is greater than a fourth threshold value .

The control based on the di f ferences of energy expenditure and/or on the di f ferences of energy expenditure gradient is used, according to the invention, for correcting the target energy expenditure , both with respect to values which concern the useful li fe period and with respect to the final cumulative value , therefore generating corrected values and curves E G, GRAD_E G with an update ( generally a downward correction, but it is also possible not to implement any downward correction i f it is not absolutely necessary, depending on the conditions described in the following) of the respective initial values defined at the beginning of the battery useful li fe .

This is due to the fact that the method according to the invention comprises a constant execution of the controls illustrated in the foregoing during the entire useful li fe of the battery, so as to monitor the energy expenditure thus avoiding early wear phenomena .

Speci fically, the method according to the invention comprises correcting downward the value of target energy expenditure gradient GRAD_E G - with a consequent downward correction of the values of energy expenditure ETG during useful li fe , upon exceeding a first number of occurrences of the condition of the di f ference between the target energy expenditure E G and the current energy expenditure L being below the first threshold value , and/or upon exceeding a second number of occurrences of the condition of the di f ference between the target energy expenditure gradient GRAD_E G and the current energy expenditure gradient GRAD_L being below the second threshold value . In addition or alternatively, it is possible to limit only the current energy expenditure L without a downward correction of gradient GRAD_E G, i . e . , by introducing a limitation of the instant energy expenditure without modi fying the values of target energy expenditure in the long term . The fashion may be decided while calibrating the system by providing, e . g . , a calibration of the number of occurrences leading to the correction, or else various ranges of overrunning within the same , wherein every range is associated with an indication of the overrunning amount .

In addition to the control and the related correcting interventions based on real-time monitoring of the current energy expenditure profile, corresponding to a reactive control mode , the method according to the invention also enables enacting a predictive control as well as a preventive control .

As regards the predictive control , referring particularly to Figure 3 , the method according to the invention comprises predicting a current energy expenditure trend L at an instant of useful li fe , i . e . , predicting - on the basis of the current operating conditions - the current energy expenditure gradient GRAD_L, and controlling a limitation of the current energy expenditure and/or a limitation of the current energy expenditure gradient , in the case of predicting an exceedance of the target energy expenditure and/or of the target energy expenditure gradient within a predetermined useful li fe interval (mileage ) , an optional communication being issued to the driver in order to inform him about the wear/ stress level caused by his driving style to the battery, and/or about an estimate of residual useful li fe of the battery i f the limitation ( s ) is/are not applied .

Figure 3 shows , at point 1 along the current energy expenditure profile L, a prediction interval comprised between a lower gradient GRAD_L_LOW, a higher gradient GRAD_L_HIGH, and prediction ranges GRAD_L_1 , GRAD_L_1 , GRAD_L_3 , mentioned in the order o f increasing values of the current energy expenditure gradient .

The method according to the invention may make use of one or more predictive algorithms which estimate, on the basis of the driving conditions and on the more or less aggressive driving style of the user, the value of the gradient GRAD_L between the extreme values GRAD_L_LOW and GRAD_L_HIGH, while also determining the classi fication thereof into one of the above-mentioned prediction ranges . Each of the ranges , according to calibration, may envisage a di f ferent correction level , which may comprise the limitation of the current energy expenditure, the limitation of the current energy expenditure gradient, or a combination of both. The limitation of the current energy expenditure may correspond, for instance, to an instantaneous cut on the electric power delivered by the battery in circumstances wherein the prediction shows a gradient GRAD_L equal to or near the value GRAD_L_HIGH, and a condition of proximity of the value of current energy expenditure L to the value ETG, SO that an intervention of mere gradient correction may not be sufficient to avoid an exceedance of the value of target energy expenditure E G for that part of useful life.

The cut on the electric power delivered by the battery may be compensated for, on systems having more than one energy source on board (hybrid systems) by selecting an alternative delivery distribution on the remaining energy sources (e.g., an engine) . In one- source systems (e.g., BEVs) , the cut on the electric power delivered by the battery leads to a limitation of the maximum allowed performance for the system. A possible elimination of the cut on the electric power delivered by the battery may be accompanied by messages to the driver, so that he may be aware of the level of wear/stress induced by his driving style on the battery, and/or of an estimate of residual useful life of the battery in case the limitation ( s ) is/are not applied.

The gradient limitation may be applied, for example, when the prediction algorithm (s) detect an evolution of the gradient in the higher ranges (e.g., GRAD_L_2 or preferably GRAD_L_3) , but the current energy expenditure is below the target energy expenditure E G by an amount sufficient to avoid exceeding the latter (exceedance is avoided by varying the gradient GRAD_L, specifically by a downward correction) .

The combination of both interventions may be chosen in intermediate conditions , e . g . , when the gradient correction may be made smoother by being combined with a more or less marked limitation of energy expenditure .

Always referring to Figure 3 and to the predictive intervention mode , on the basis of the method according to the invention it is possible - under given conditions - to predict an energy expenditure trend at an instant of useful li fe , and to enable an increase in the current energy expenditure and/or an increase in the current energy expenditure gradient i f a predetermined interval of useful li fe preceding said instant has been exempt from conditions of di f ference between the target energy expenditure and the current energy expenditure L below the first threshold value ( or below a further adj ustable threshold value ) and/or of conditions of di f ference between the target energy expenditure gradient GRAD_E G and the current energy expenditure gradient GRAD_L below a second threshold value ( or below a further adj ustable threshold value ) .

In this regard, let us cons ider the energy expenditure L at instant n, in the right part of the diagram of Figure 3 . It may be observed that the point on the curve of current energy expenditure at instant n is preceded by an evolution characteri zed by low values of current energy expenditure L and low values of gradient GRAD_L . In such conditions , it is possible to enable - so to say - a performance "bonus" in favour of the user, wherein the bonus may envisage an exceedance of the target energy expenditure E G and/or o f the gradient GRAD_E G , due to the substantial absence of operating conditions adapted to generate signi ficant degradation phenomena in the preceding useful li fe interval .

To this purpose , the references GRAD_L_LOW' and GRAD_L_HIGH' identi fy, in the diagram of Figure 3 , the two extreme prediction values mentioned in the foregoing (while the values GRAD_L_1 ' , GRAD_L_2 ' and GRAD_L_3 ' correspond to the prediction ranges intermediate between GRAD_L_LOW' and GRAD_L_HIGH' ) , referred only to instant n, but the value GRAD_L_HIGH' in this case is higher than the value GRAD_E G, thereby indicating that , in the absence of operating conditions which may generate signi ficant degradation phenomena in the preceding useful li fe interval , it is possible to temporarily of fer to the user an additional energy availability, without entering an area of the diagram comprised between the curves E G and EMAX (both at the beginning of useful li fe and with the values corrected during the battery useful li fe ) , since the respective end-of-li fe proj ections PROJ_L, PROJ_L' in any case converge to the target value AEo ( the initial value or a value updated during the battery useful li fe ) at end of li fe . The diagram area comprised between the curves E G and E X , which in the known managing methods represents a normal operating field, in the method according to the invention is used only to enable short extra deliveries of energy, or in general for temporary operating conditions which enable fixing prediction errors of the evolution of the current energy expenditure GRAD_L .

As regards preventive control , the method according to the invention also allows for a downward correction of the cumulative end-of-li fe values of the target energy expenditure E G_EOL and/or of the target energy expenditure gradient GRAD_E G .

This sort of intervention is implemented when, at a given useful l i fe instant , it is determined that the cumulative current energy expenditure L compared with the end-of-li fe available energy expenditure yields a ratio of the current State of Health ( SoH) value of the battery to the value thereof which is presumed at end of li fe other than a target value , particularly below a threshold value . This also means that the updating of the calibration parameters of the method according to the invention takes place by means of a recurring and frequent cross reference to a SOH-time ( or, alternatively, SOH-mileage ) plan, so as to ensure that the correcting/ limiting interventions that are carried out and/or the predictions supporting the inferences of the method according to the invention refer to the correct targets ( for example the AE - mileage energy expenditure map does not take into account the battery degradation due to stopovers , hence the need to periodically realign the values by taking into account the SOH or SOHe ) .

Referring to Figure 4 , the block diagram represented therein shows in the most general way the logic structure of the method according to the invention, adding thereto the references to the functional configuration of a vehicle having an at least partly electrically powered drive train .

Reference EBX denotes an estimate and prediction functional element , which implements the method according to the invention on a vehicle . Typically, the element EBX may correspond to a control unit or a calculation module of a control unit installed on board the vehicle . As exempli fied in the diagram of Figure 4 , reference BC denotes the data input into the element or block EBX : such data are - without limitation - the current mileage ( km or mi ) of the vehicle , the current driving time and the end of travel instant , the current State of Health SOH and the SOH limit values ( e . g . , the map of the limit curve LC ) . As regards the data relating to the end of travel , they are made available by the control units generally provided on modern vehicles , without requiring the addition of a navigation system . The addition of a navigation system, however, may make the predictive processing even more accurate ( at the expense of a higher complexity) . The reference ED denotes a set of data which are formed and/or stored during the execution of the method according to the invention, and which comprise - without limitation - a history of the energy expenditure depending on the mileage ( corresponding to the cumulative value of the current energy expenditure L ) , the predictions of the energy expenditure gradient GRAD_L, the position of the points of the current energy expenditure profile ( LI , Ln, for example ) with respect to the limit curves ( ETG, for example ) , and the parameters for managing the target energy expenditure E G as a function of the residual SOH ( i . e . , the interventions of updating E G or GRAD_ETG at the instant of cross-checking on the basis of SOH or SOHe , as described in the foregoing) .

The output data set of the element/block EBX is associated with reference EPS_IN, depicted in Figure 3 which represents all the interventions that the method according to the invention accomplishes , such interventions being directly reflected in the energy delivered by the battery .

Reference EPS_C generally denotes a typical controller and manager of the power flows in an electric powertrain; such a controller determines the power which a battery or a battery set delivers to the vehicle via the powertrain . The general controller EPS_C receives the input data set EPS_IN, and delivers a signal or data set EPS_OUT to a powertrain PT , wherein the signal or the data set EPS_OUT corresponds to driving the powertrain according to the predictions and the limits resulting from the determinations of the method according to the invention . EPS_IN may optionally be integrated into EPS_C, i f it is not a physically separated node .

Thanks to the method according to the invention, it is possible to control the exploitation of the battery or the battery set in a motor vehicle while supporting, as much as possible , the perception by the user of constant performance throughout the useful li fe , or in alternative , by means of instant warnings to the driver, it is possible to give visibility or awareness about the degree of wear/ stress induced in the battery by the driving style and/or about an estimate of the residual useful li fe of the battery, i f the limitation ( s ) is/are not applied .

The target energy expenditure E G is an operating limit with constant or nearly constant gradient , which doses the performances of the battery or battery set and avoids marked variations thereof , as it would be the case of an operation within the curve of limit energy expenditure EMAX in the case of known methods . As observed in the foregoing, the area comprised between the curve E X and the curve E G is a working area for the battery or battery set only for the purpose of correcting prediction errors or concessions to the user after a period of a particularly correct driving style , but it does not correspond in any way to an admissible operating area on a continuous basis , according to the invention . As it is evident from the description provided in the foregoing, the invention aims at stabili zing, as much as possible , the current energy expenditure gradient GRAD_L, and at avoiding, as much as possible , the exceedance of gradient GRAD_E G , i . e . , avoiding exceeding a condition which guarantees a uni form delivery from the beginning to the end of the useful li fe , and a consequent perception of uni form performance by the user .

Of course , the implementation details and the embodiments may amply vary with respect to what has been described and illustrated in the foregoing, without departing from the scope of the present invention as defined in the annexed claims .

Claims

1. A method for managing an automotive battery, including : defining a maximum allowed total energy expenditure (AEo) of the battery for a battery useful life interval, defining a limit allowed energy expenditure profile (EMAX) over the useful life interval, said limit allowed energy expenditure profile (E X) being increasing up to the value of said maximum allowed total energy expenditure (AEo) of the battery

- defining a target energy expenditure profile (ETG) which develops over the useful life interval, said the target energy expenditure profile (E G) being increasing up to the value of said maximum allowed total energy expenditure (AEo) of the battery and defining a gradient of target energy expenditure (GRAD_E G) over said useful life interval,

- monitor a current energy expenditure (L) of the battery during the useful life interval, said current energy expenditure (L) defining a current energy expenditure gradient (GRAD_L)

- comparing the current energy expenditure (L) at an instant of the useful life with the target energy expenditure (E G) of said target energy expenditure profile (ETG) at the same instant of the useful life, and/or comparing the current energy expenditure gradient (GRAD_L) at an instant of the useful life with the target energy expenditure gradient (GRAD_ ETG) at the same instant of the useful life,

- if a difference between the target energy expenditure (ETG) and current energy expenditure (L) is less than a first threshold value and/or if a difference between the target energy expenditure gradient (GRAD_ETG) and current energy expenditure gradient (GRAD_L) is less than a second threshold value, controlling a limitation of the current energy expenditure limitation (L) and/or a limitation of the current energy expenditure gradient (GRAD_L) , respectively.

2. The method of Claim 1, further comprising allowing an increase in current energy expenditure (L) and/or an increase in current energy expenditure gradient (GRAD_L) if, respectively, a difference between the target energy expenditure (E G) and the current energy expenditure (L) is greater than a third threshold value and/or if a difference between the target energy expenditure gradient (GRAD_E G) and the current energy expenditure gradient (GRAD_L) is greater than a fourth threshold value.

3. The method of Claim 1 or Claim 2, further comprising updating the value of the maximum allowed total energy expenditure (AEo) and/or the value of the target energy expenditure gradient (GRAD_E G) upon exceeding a first number of occurrences of the condition of the difference between the target energy expenditure (GRAD_E G) and the current energy expenditure (L) being below the first threshold value and/or upon exceeding a second number of occurrences of the condition of the difference between the target energy expenditure gradient (GRAD_E G) and the current energy expenditure gradient (GRAD_L) being below the second threshold value .

4. The method of Claim 1 or claim 2, further comprising updating the maximum allowable total energy expenditure value (AEo) and/or the target energy expenditure gradient value (GRAD_E G) if a current energy expenditure (L) accrued up to an instant of the useful life results in a value of a ratio of a current State of Health SoH of the battery to an allowable State of Health of the battery at the end of its life other than a target value, particularly below a threshold value.

5. The method of Claim 1 or Claim 2, further comprising predicting a current energy expenditure trend (L) at an instant of the useful life, and controlling a limitation of the current energy expenditure (L) and/or a limitation of the current energy expenditure gradient (GRAD_L) in the case of predicting an exceedance of the target energy expenditure (ETG) and/or the target energy expenditure gradient (GRAD_ETG) within a predetermined useful life interval.

6. The method of claim 1 or claim 2, further comprising permitting an increase in current energy expenditure (L) and/or an increase in current energy expenditure gradient (GRAD_L) in case a predetermined useful life interval preceding said instant has been exempt from conditions of difference between target energy expenditure (E G) and current energy expenditure (L) below the first threshold value and/or conditions of difference between target energy expenditure gradient (GRAD_E G) and current energy expenditure gradient (GRAD_L) below the second threshold value.

7. The method of claim 1, comprising issuing a communication directed to a driver when a difference between the target energy expenditure (E G) and the current energy expenditure (L) is less than a first threshold value and/or if a difference between the target energy expenditure gradient (GRAD_ETG) and the current energy expenditure gradient (GRAD_L) is less than a second threshold value, wherein said communication includes informing the driver of a stress imposed on the battery and/or providing an indication of the remaining battery life in the absence of said limitation of the target energy expenditure gradient (L) and/or limitation of the current energy expenditure gradient (GRAD_L) .

8. The method of Claim 5, comprising issuing a communication directed to a driver when the value of a ratio of a current State of Health SoH of the battery to an allowed end of life State of Health SoH of the battery is different from a target value, particularly below a threshold value, wherein said communication includes informing the driver of a stress imposed on the battery and/or providing an indication of the remaining battery life in the absence of said stresses, and providing a limitation of the current energy expenditure (L) and/or a limitation of the current energy expenditure gradient (GRAD_L) in the event that the target energy expenditure (ETG) and/or the target energy expenditure gradient (GRAD_E G) is predicted to be exceeded within a predetermined lifetime range.

9. The method according to claim 1, wherein said target energy expenditure gradient (GRAD_E G) along said useful life interval is defined based on of past driving data and subsequent prediction of probable future driving .

10. The method of claim 3 or claim 4, wherein said updating the maximum allowable total energy expenditure value (AEo) and/or the target energy expenditure gradient value (GRAD_E G) comprises a downward correction of the maximum allowed total energy expenditure value (AEo) and/or of the target energy expenditure gradient value (GRAD_E_TG) .