OPTIMIZATION OF THE AXLE DISTRIBUTION STRATEGY IN A BEV

Abstract

Methods and devices are provided for online optimization of the axle distribution strategy in a battery electric vehicle (BEV) with more than one drive axle.

Claims

1. A method for optimizing torque distribution in a drive system of a battery electric vehicle, which has more than one drive axle and a number n of e-machines driving the drive axles, the method comprising: using a control unit to calculate a power loss of each e-machine i for the torque distribution and determine a minimum of a total power loss P.sub.V,ges of the drive system; using the control unit to control the e-machines i so that they jointly M.sub.Anf provide a torque requested, each e-machine i generating in each case a torque M.sub.i determined for the minimum of the total power loss P.sub.V,ges and assigned to it; wherein, when there is a torque request M.sub.Anf, in each case a value P.sub.V0,i for current drag losses and a factor K.sub.Phi,i for a current operating point is transmitted to the control unit from each of the e-machines i, and the control unit calculates the power loss of each e-machine i according to:
P.sub.V,i=P.sub.V0,i+K.sub.Phi,i*M.sub.i.sup.2, the total power loss of the drive system calculated according to:
P.sub.V,ges=Σ.sub.i=1.sup.nP.sub.V,i. and the minimum of the total power loss is determined by varying the torques M.sub.i of the individual electric machines i, according to:
M.sub.Anf=Σ.sub.i=1.sup.nM.sub.i.

2. The method according to claim 1, wherein a number of driven axles is two.

3. The method according to claim 2, wherein the number n of e-machines is two.

4. The method according to claim 2, wherein the number n of e-machines is four.

5. The method according to claim 1, wherein the determination of the minimum of the total power loss P.sub.V,ges of the drive system takes place in real time.

6. A drive system of a battery electric vehicle, comprising: more than one drive axle; a number n of e-machines driving the drive axles; and a control unit for torque distribution, which is set up to calculate a power loss of each of the e-machines, and, when there is a torque request M.sub.Anf, to determine a minimum of an associated total power loss P.sub.V,ges of the drive system, and then to control the e-machines in such a way that they jointly provide the requested torque M.sub.Anf, each electric machine i generating a torque M.sub.i determined for the minimum of the total power loss P.sub.V,ges and assigned to it; wherein, when there is a torque request M.sub.Anf, the e-machines i in each case transmit a value P.sub.V0,i for the current drag losses and a factor K.sub.Phi,i for the current operating point to the control unit, and the control unit calculates the power loss of each e-machine according to P.sub.V,i=P.sub.V0,i K.sub.Phi,i*M.sub.i.sup.2.

7. The drive system according to claim 6, wherein the number of driven axles is two.

8. The drive system according to claim 7, wherein the number n of e-machines is two.

9. The drive system according to claim 7, wherein the number n of e-machines is four.

10. The drive system according to claim 5, wherein the control unit comprises an optimizer for determining the minimum of the total power loss P.sub.V,ges in real time.

Description

DETAILED DESCRIPTION

[0009] According to some embodiments of the invention, when there is a torque request M.sub.Anf, a value P.sub.V0,i for the current drag losses and a factor K.sub.Phi,i for the current operating point are transmitted to the control unit from each of the electric machines i, and the control unit calculates the power loss of each electric machine i according to:

P.sub.V,i=P.sub.V0,i+K.sub.Phi,i*M.sub.i.sup.2,

calculates the total power loss of the drive system according to:

P.sub.V,ges=Σ.sub.i=1.sup.nP.sub.V,i,

and determines the minimum of the total power loss by varying the torque M.sub.i of the individual e-machines i, where applies:

M.sub.Anf=Σ.sub.i=1.sup.nM.sub.i.

[0010] The optimal distribution is determined by an online calculation of the power losses of the various torque distributions on the axles. For this purpose, a value for the current “drag losses” (P.sub.V0) and a factor for the current operating point (K.sub.Phi) are transmitted from each drive machine to the axis distribution strategy, with the help of which the losses can be calculated at runtime. Here, online means that the values are determined at runtime in real time without the use of characteristic maps or characteristic curves or other static data.

[0011] The calculation takes into account that the power loss of an e-machine follows a simple quadratic equation depending on its current operating point and its machine constants. P.sub.V0 represents the power loss at “no load,” K.sub.Phi is the factor for the current operating point, which the power electronics of the respective e-machine calculates based on its machine constants and the current load point. It is equal to the difference between the total power loss and the no-load power loss divided by the square of the actual torque. The two values P.sub.V0 and K.sub.Phi are each formed by the power electronics of the respective e-machine, since the information about machine constants, current speed, current temperature, current voltage and air gap is available here anyway because it is required for the operation of the e-machine. The two values P.sub.V0 and K.sub.Phi also include the speed, rotor temperature, stator temperature, current operating voltage and the resistance of the respective e-machine caused by the air gap.

[0012] With this information, the control unit can calculate the total losses for different torque distributions online and determine a minimum, with different torques M.sub.i being tried out in an optimizer. The lowest total loss can be found by summing up all machines. The torque that led to the lowest total loss is output as the target torque for the respective e-machine. In one embodiment of the method the minimum of the total power loss P.sub.V,ges of the drive system is determined in real time.

[0013] In one embodiment of the method, the number of driven axles is 2.

[0014] In one embodiment of the method, the number n of e-machines is 2. In another embodiment of the method, the number n of e-machines is 4, i.e., each wheel of the vehicle is driven by an assigned e-machine (all-wheel drive).

[0015] Some embodiments of the invention also relate to a drive system for a battery electric vehicle (BEV), which has more than one drive axle and a number n of e-machines driving the drive axles, and a control unit for torque distribution, which is set up to calculate the power loss of each of the e-machines, and, when there is a torque request M.sub.Anf, to determine a minimum of the associated total power loss P.sub.V,ges of the drive system, and then to control the e-machines in such a way that they jointly M.sub.Anf provide the requested torque, each e-machine i generating in each case the torque M.sub.i determined for the minimum of the total power loss P.sub.V,ges and assigned to it, characterized in that, when there is a torque request M.sub.Anf, the e-machines i transmit in each case a value P.sub.V0,i for the current drag losses and a factor K.sub.Phi,i for the current operating point to the control unit, and the control unit calculates the power loss of each e-machine i according to P.sub.V,i=P.sub.V0,1+K.sub.Phi,i*M.sub.i.sup.2,

[0016] In one embodiment, the control unit of the drive system comprises an optimizer for determining the minimum of the total power loss P.sub.V,ges in real time.

[0017] In one embodiment of the drive system, the number of driven axles is 2.

[0018] In one embodiment of the drive system, the number n of e-machines is 2. In another embodiment, the number n of e-machines is 4.

[0019] By the online optimization, the torque distribution to the drive axles (axle distribution strategy) can be implemented using standard software, and there is no need to develop an application for each drive variant. This approach is less error-prone and no concessions have to be made that could have a negative impact on efficiency. The online optimization achieves more precise results, since not all dependencies can be mapped in any level of detail with the static approach.

[0020] German patent application no. 10 2021 117561.5, filed Jul. 7, 2021, to which this application claims priority, is hereby incorporated herein by reference, in its entirety. Aspects of the various embodiments described above can be combined to provide further embodiments. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled.