Method, apparatus and system for discharging battery modules

Abstract

a method of controlling discharging of a plurality of battery modules 101a-d through a plurality of power convertors 105a-d. Each power converter is connected across a particular battery module of the

Description

FIELD OF THE INVENTION The present invention relates to a method and apparatus for discharging battery cells, or modules containing groups of battery cells. BACKGROUND OF THE INVENTION The widespread adoption of high capacity / power batteries in battery systems within vehicles and buildings has been instrumental in reducing greenhouse gas emissions by storing electricity from traditional and renewable sources, thereby reducing reliance on fossil fuels. However, these battery systems have a finite lifespan, and so as the number of batteries installed increases, effectively managing the disposal of end-of-life batteries has become a significant challenge that requires efficient practices to prevent hazardous waste, protect the environment, and increase recycling of the energy and / or materials used. To avoid the need for landfill disposal and to recover valuable materials, it is essential to recycle end-of-life batteries. Before recycling batteries, it is critical to stabilise the batteries as a safety precaution in the materials reclamation process. However, the fast and efficient stabilisation of end-of-life batteries presents a challenge for recycling technologies due to residual energy, which can lead to thermal runaway, posing safety hazards and uncontrolled fires during the mechanical processing steps. It would also be beneficial to be able to recover any residual energy before recycling. SUMMARY It is an object of the present disclosure to provide a means to safely discharge end-of-life battery cells, or groups thereof. BRIEF DESCRIPTION OF THE DRAWINGS Examples of the invention are further described hereinafter with reference to the accompanying drawings, in which: Figure 1 shows an overview of a battery discharging system according to an example of the disclosure; Figure 2 shows a half-bridge Buck converter based battery discharging apparatus according to an example of the disclosure; Figure 3 shows a microcontroller based implementation of controlling the Buck convertors of Figure 2, according to an example of the disclosure; Figure 4 shows a high level schematic of an apparatus for discharging a plurality of battery cells, according to an example of the disclosure; Figure 5 shows an example individual battery cell insertion by a half-bridge Buck converter, according to an example of the disclosure; Figure 6 shows an example individual battery cell bypass by a half-bridge Buck converter, according to an example of the disclosure; Figure 7 shows how a plurality of battery cells may be inserted, according to an example of the disclosure; Figure 8 shows how a plurality of battery cells may be bypassed, according to an example of the disclosure; Figures 9A-9D show how splitting functions, a,, are transformed to new splitting functions, ai-new, according to an example of the disclosure; Figure 10 shows a battery voltage translation function for use in the disclosed method(s), according to an example of the disclosure; Figure 11 shows a high level schematic of a first example battery cell discharging method, according to an example of the disclosure; Figure 12 shows a first way to derive the initial splitting functions, a, derived from battery state parameters, according to an example of the disclosure; Figure 13 shows how the value of n used in the method is derived, according to an example of the disclosure; Figure 14 shows a SOC averaging function, according to an example of the disclosure; Figure 15 shows a battery cell capacity averaging function, according to an example of the disclosure; Figure 16 shows a first example of how values of the scaling factors (0 / ) are derived, according to a first example of the disclosure; Figure 17 shows a first k-clamp function based on SOC, according to an example of the disclosure; Figure 18 shows an alternative way to derive the initial splitting functions, ®, derived from battery cell terminal voltages, according to an example of the disclosure; Figure 19 shows a second k-clamp function based on terminal voltages, according to an example of the disclosure; Figure 20 shows a more detailed implementation of an apparatus for implementing the battery discharging control method, according to an example of the disclosure. DETAILED DESCRIPTION The technical operation and advantages of the present disclosure shall now be provided by way of a plurality of examples that are merely illustrative of the novel and inventive features, and the disclosed examples are intended to be fully combinable in any reasonable combination. In the following disclosure, the examples are described in the context of discharging one or more battery cells. However, it will be appreciated that examples of the disclosure may be used to discharge one or more battery cells in any form of battery cell arrangement or grouping, for example individual or multiple battery cells, connected in series or parallel. These singular or multiple battery cell arrangements may be referred to as battery modules, or simply as a battery, i.e. a battery module may comprise a single cell (or multiple cells). As such, the following may use battery(ies), battery cell(s) and mattery module(s) interchangeably. Examples of the present disclosure provide a state-of-the-art battery discharging system including a novel energy management system, that utilises advanced power electronics and intelligent battery discharging control algorithms. The disclosed examples enable pulse discharging based on battery energy levels, whilst also offering regulated DC voltage output for energy recovery. Examples may be equipped with integrated sensors for real-time monitoring and a bypass mechanism for isolating / disconnecting faulty (or just depleted) batteries, which may ensure continuous and safe discharge. Figure 1 shows an overview of the disclosed battery discharging system 100 according to an example of the disclosure. This example comprises a plurality of battery cells 101, coupled to the Energy Management System (EMS) 400 according to an example of the disclosure, in such a way to allow the EMS 400 to carry out the disclosed discharging method(s) across a DC Load 120. In some examples, the EMS 400 may be coupled 125 to state parameter sensors coupled to the one or more battery cells 101, such as state of charge sensors, and the like, or may be connections to allow direct sampling of a relevant parameters, for example voltage. As can be seen, the system 100 as viewed in the wider context may include a DC side 110, and an AC side 130, between which is coupled the DC Load 120. The DC side may also include a plurality of DC regulators 105, which operate as disclosed in more detail below. The DC regulators 105 may also be referred to as DC-DC convertors. The output of the DC side, coming from the DC regulators 105, may be coupled to an invertor 140 on the AC side, which may allow conversion of the output DC voltage into AC, for example, for re-using the energy extracted from the discharging battery cells 101, for example by feeding into a local energy network 150. In figure 1, there is also shown some feedback 135 from the AC side to the DC side, which may be used for additionally controlling the method. Specific examples of the EMS 400 according to an example of the disclosure may utilise a half bridge topology and a modular structure to fix (i.e. set) the voltage of the discharging batterie cells 101, which enables the proposed system to both reduce the size of the subsequent power electronics (e.g. DC regulator 105 and inverter 140), as well as take power directly from the discharging circuitry to charge a DC load 120, such as a DC battery storage system. This subsequent reuse of the discharged battery energy may either reduce costs or reduce losses across the systems in place in a battery discharging facility. Other examples (not specifically disclosed herein) may use other convertor topologies - i.e. the disclosure is not limited to the Buck converter of the examples. Examples of the disclosed discharging control methods use the terminal voltages of each of the battery cells 101 being discharged, to determine (i.e. calculate) the discharging of each of the battery cells 101, and may be used when the State of Charge (SOC) profile and / or State of health (SOH) / capacity (nominally rated and / or after applying SOH degradation) of one or more of the battery cell(s) 101 being discharged is not known. Examples using the SOH may be used when discharging battery cells or modules of the same form factor. Further examples of the disclosure additionally may use the change in battery cell output Voltage during the discharge cycle, along with the initial State of Charge to determine which method to use to discharge the battery cells / modules 101. Furthermore, in still further examples, by adding in the use ofthe change in Voltage (on top of the SOC) to control the discharge process, a combined example discharging apparatus is able to include additional safety checks for when the SoC of one or more battery cells 101 has been incorrectly estimated, as well as giving additional control for the user to set a suitable / desirable output terminal voltage (i.e. an output voltage that may be used a downstream DC battery storage system, or other load that may be powered off the discharge voltage). Examples of the disclosure follow a power flow design principle, in which the energy flow channels into a unidirectional path, where battery cells either send power to the DC load 120 during discharge or receive power from the DC load 120 during charge, therefore streamlining the power flow. Each energy flow pathway in a power flow design should be appropriately rated to meet the specific requirements ofthe overall system (e.g. current rating, voltage rating, etc), thus eliminating excess rating (and hence cost). This careful rating of pathways ensures a single, efficient route for power delivery is employed, thereby enhancing operational efficiencies. Therefore, according to an example, an integrated modular equalisation scheme as will now be described is used, where battery cell energy is directly tied to the load without battery power circulating within an equalising system. Figure 2 shows a half-bridge Buck converter based battery discharging circuit 200 according to an example ofthe disclosure. In Figure 2, there is shown a modular multilevel converter (MMC) structure that may be used to provide an energy management apparatus utilising a Buck discharge strategy. According to examples, the Buck converters 105a-d may be realised using synchronous rectification (SR), using MOSFET switches, e.g. S1 201 and S2 202, coupled as shown at circuit level detail 210 (note: item 210 technically shows both the individual switches ofthe buck convertor, as well as the respective battery cell being discharged via that Buck converter). This approach offers various advantages, including the elimination ofthe MOSFET switch diode's 203 forward voltage drop, which significantly reduces power losses and improves efficiency. In addition, SR offers faster switching times, resulting in less switching losses, decreased EMI noise, and enhanced thermal performance. The overall proposed battery discharging apparatus of Figure 2 is comprised of a succession of half-bridge converters 105a-105d, each of which is connected across a separate battery cell to be discharged 101a-101d, where there are as many half-bridge converters 105 as battery cells 101, and where the battery cells 101 are connected in series (a.k.a. in an independent input and output series, IIOS, configuration). Figure 2 also shows an output global LC filter, which is typically used in a Buck converter, and which has been strategically relocated to serve as a global filter (Lo 220 and Co 240) on the DC bus side and, therefore, Figure 2 as a whole can be viewed as a multi-input Buck converter. Using a (effective) global filter topology allows to reduce the effects of voltage drop on the overall system efficiency. This is because the current rating of inductors is a function of their DC resistance and inductance, so organising the converters in an IIOS architecture with multiple inductors in series, would increase the conductive losses, resulting in a decrease in efficiency, whereas organising in a global topology reduces the overall total conductive losses. Figure 2 also shows the load current, Load, 230, and overall output voltage for the voltage bus, Vbus 250, which are used to control the method, as described in more detail below. Figure 3 shows a centralised control architecture based implementation of controlling the Buck convertors 105 of Figure 2, according to an example ofthe disclosure. This example utilises a centralised microcontroller 310, as shown in Figure 3, to carry out the disclosed discharging control method, in which the discharge of a particular (i.e. given) number of battery cells / modules 101a-d via respective Buck converters 105a-d are controlled in real-time by a single microcontroller 310. This example centralised microcontroller architecture for the battery cell discharge controller (including Bus voltage controller) incorporates a control method as described in detail below, and may use sensor data collected for (or from) state of charge estimate computations. While the disclosed MMC architecture 200 theoretically allows for the management of an extensive number of battery cells 101, in practice, the centralised control approach may be bounded by the microcontroller's I / O capacity, therefore restricting the disclosed discharging control method to a predefined number of battery cells 101. Accordingly, in other implementations (not shown), a distributed modular control technique may be used instead, in which battery cells 101 are governed in smaller groups that collaborate. Such techniques may use a communication bus to share cell state information, which can serve as inputs to the primary equalisation method (wherein this equalisation is part of a wider battery discharging control method, described in detail below) carried out by the battery cell discharge controller (including Bus voltage controller). The modular approach would provide scalability for the overall discharging apparatus and system. An alternative is the integration of a microcontroller with an FPGA, in order to balance control capacity with system complexity while preserving the efficiency of the centralised structure. Examples provide a battery discharging control method that includes a novel state equalisation control method portion for use in controlling the discharge of a plurality of battery cells 101 through a plurality of DC-DC convertors, e.g. Buck converters 105, that actively distributes a load demand to each battery cell's respective Buck converter in proportion to each battery cell’s state mismatch (e.g. battery cell output / terminal voltage, state of Charge, State of Health, or any other characterising parameters) mismatch). In this way, the disclosed discharging control method promotes state equalisation between the different ones of the plurality of battery cells 101 by assigning a higher proportion of the load demand to stronger battery cell(s) and a lower proportion to weaker battery cell(s), thus forcing the states to converge during discharge. In some examples, reference to states that are 'strong(er)’ and 'weak(er)’ refer to characterising parameters of the battery cells including, but not limited to: battery cell(s) State of Charge (SOC), battery cell(s) capacity and battery cell(s) terminal voltage. The underlying mechanisms of the disclosed methods and apparatuses also allow the battery discharging apparatus to act as a regulated voltage source in an over all system, thereby facilitating the re-use of battery cell energies recovered by the disclosed battery discharging control method (and associated apparatus to carry out the disclosed method), for example by use with a secondary load (i.e. allows redirection / repurposing of the energy stored in the battery cells 101 being discharged) and hence enabling energy recovery. As shown in Figure 1, this may be done by outputting the energy through an AC comprising, for example, an invertor 140, into a local energy network 150. In some examples, the spread of the state variable SOC may determine how the discharging control method responds. As such, in some examples, individual battery cell capacity information may also be determined prior to the discharge of the battery cells 101, for example by using coulomb counting capabilities known in the art. In such examples, a mixed source stock of battery cells with varying capacities may still be used, thereby providing for discharge methods (and associated apparatuses) that can handle a broad range of source battery cell characteristics. Output Bus Voltage (Vbus) As will be appreciated, examples of the disclosure provide an output DC bus voltage, Vbus 250 derived from the battery cells being discharged. According to examples, a Bus voltage controller portion is used to regulate the output DC bus voltage, Vbus 250, which in some examples may be achieved by using a cascaded closed looped controller 420 as show in the top half of Figure 4. This example comprises two Proportional Integral (PI) controllers 423 and 427, but other examples may use different proportional controllers, such as P, PD, PID or the like - i.e. any suitable closed loop controller. In this example, the cascaded closed looped based Bus voltage controller 420 comprises an outer voltage loop portion 420a and an inner current loop portion 420b. The cascaded closed looped controller based Bus voltage 420 may operate by comparing, via first comparator 421, a specified output DC bus voltage, Vbus 250, to the sensed (i.e. actual, at this point in time) output voltage, VBus~sense 422 and then compensating for the error (shown as parameter Ve), which is used by a first PI 423 to form the inductor current demand, demand 425, so that the outer voltage loop portion 420a is able to control the output DC bus voltage, Vbus250. The output of the outer voltage loop portion 420a serves as the demand for the inner current loop portion's 420b reference value (Idemand 425) for the inductor 220 current (Load 230), which is compared to a sensed current (Lense 426) using second comparator 424, to form parameter Ie, which is passed through a second PI 427 and a delay block 428 (which delays the current sample by a predetermined time period, e.g. by 1 time period, to account for microcontroller delay, if and where applicable) to form Db 430, having a duty cycle (see below discussion of the duty cycle). By comparing the inductor current demand, Lemand 425, to the sensed inductor value, Lense 426, the inner current loop portion 420b is able to control the inductor 220 current (Load 230). This ensures that the inductor current is controlled in accordance with the demand of the load 120. To maintain the desired output bus DC voltage Vbus250 level and ensure that the load 120 is supplied with the required amount of current (Load 230), the bus voltage controller 420 uses the cascaded closed-loop controller to control the inductor current and output DC bus voltage VbUs250. According to some examples, the duty cycle, Db 430, produced at the net output of the Bus voltage controller 420 is used to request the required current from a voltage source. This, in turn, controls the amount of charge delivered to the load 120, and is used for compensation against output voltage drops. Since a multilevel Buck converter system is used to manage the plurality (i.e. multiple) battery cells 101 being discharged, the requested current demand is provided in the form of a duty cycle, which is split and distributed to each individual battery cell Buck converter(s) 105 via a control methodology, as shown generically in Figure 4. This control methodology comprises taking individual battery cell states 410 as inputs to the battery cell discharge controller 440 carrying out the method, which provides a set of adapted splitting coefficients (ai.new - an-new), as described in more detail below. These adapted splitting coefficients are used to provide respective Pulse Width modulated signals (PWMi-PWMn, 470-472) via a plurality of multipliers 450-452, each serving one of the top switches in the respective Buck convertors (S1, S3, S5, etc), and a plurality of limiting circuits 460-462, which are also called saturation blocks that operate to prevent over and under modulation. Thus, the proposed discharging method produces a loop multiplier, or a coefficient, for the bus duty cycle, Db 430, essentially scaling the current demand, and therefore voltage demand from each battery cell 101 being discharged. For instance, according to the disclosed voltage sharing principle, the Bus voltage controller 420 regulates the DC bus voltage Vbus 250 by balancing the voltage contributions from each Buck converter 105 (across each individual battery cell 101). Figure 5 shows a schematic representation 500 of an individual battery cell insertion by a half-bridge Buck converter, according to an example of the disclosure. In Figure 5, the Buck convertor comprises a first switch (e.g. MOSFET transistor) S1, 201, and a second switch (e.g. MOSFET transistor) S2, 202, coupled to the battery cell 101. In this figure, S1, 201 is on, whilst S2, 202, is off, so the battery cell 101 is coupled to, i.e. inserted into, the wider circuit, and able to contribute energy (i.e. be discharged). Figure 6 shows a schematic representation 600 of an individual battery cell bypass by the half-bridge Buck converter, in the opposite situation to Figure 5, where switches S1 201 and S2 202 are in the opposite switched state to Figure 5 (i.e. S1 is off, and S2 is off), so that the respective battery cell is being by-passed (i.e. isolated from the wider circuit). Figure 7 shows the cumulative effect of all Buck convertors in a MMC switching their respective battery cells into the circuit (i.e. all battery cells are being inserted 500). Figure 8 shows the cumulative effect of all Buck convertors in a MMC switching their respective battery cells out of the circuit (i.e. all battery cells are being bypassed 600). Note, in both Figures 7 and 8, the top switches of each of the respective Buck convertors are numbered S1, S3, S5, etc, and the bottom switched are numbered S2, S4, S6, etc. Basic Principles of operation The basic principle of operation is based on switching states according to the following table: Table 1 Half Bridge Switching States S1,S3, S5, etc S2, S4, S7, etc State 1 1 0 State 2 0 1 It is notable that there are only two distinct switching states, namely cell insertion 500 and cell bypass 600, which are summarised in the above Table (in most examples, there is no condition allowed whereby both switches are activated at the same time, which may be ensured by use of Dead Time, discussed below). As indicated in Figure 5, the procedure for cell insertion 500 involves the activation of the upper side switch, labelled S1, and the deactivation of the lower side switch, labelled S2, akin to complimentary switching. This permits the battery cell involved to be connected in series with the other battery cells and to the load. In addition, by modulating S1 on and off at a high frequency (e.g. using PWM), it is possible to control the charge delivered to the load in accordance with Equation (1) and achieve the time-averaged output voltage described by (2) - Charge flowing out of the battery cell, which is a function of the battery current (lbat) denoted by: Qbat - IbafD.Ts (1) — 1 Ts voi(t) dt t°n y, = [) y. Ts According to examples, these inherent properties can be effectively exploited to regulate the DC bus voltage, Vbus 250, and through the control of charge delivery by each battery cell 101, state equalisation can be attained, as described in more detail below. Figure 6 depicts the process of battery cell bypass 600, which entails deactivating S1 while activating S2, thus disconnecting the battery cell 101 from the load without interrupting the current flow between adjacent cells. This feature can also be exploited to include fault tolerance into the discharge control scheme, by allowing faulty / already depleted battery cells to be bypassed safely, hence improving the overall system's reliability. Figure 7 shows a schematic representation 700 of how a plurality of battery cells 101 may be inserted or bypassed, in this case all inserted 500, according to an example of the disclosure, in particular illustrating the switching action detailing the current flow for an example 4-cell configuration. In this Figure, there is shown a Buck convertor per battery cell. In this idealised scenario, all cells are switched into the load by activating the respective higher side switches (S1, S3, S5, S7) and deactivating the respective lower side switches (S2, S4, S6, S8). For example, this may happen during pulse on period, which may be defined as the product of the duty cycle (Db 430) of Figure 4, and a time period, Ts - i.e. the product DbTs. In this multiple battery cell example, n is the number of battery cells involved (this nomenclature will be used throughout the disclosure), and the net duty cycle required at the bus side (¾) fora bus voltage (Vbus) can be defined as: y, D1=D3=D3 = - = Dn = DB=-^~ (3) nvcell During this period the inductor charges up to: ■ । 1, -1-- (4 bLave 1 2 ' Where iLave is the average load current, and is the ripple current. Conversely, during the pulse off period (which is defined as (1-DB)TS), the inductor’s current falls to: Lave 2 The ripple current can be approximated as a percentage of the output load current △k = %hoad (6) Accordingly, by predefining the maximum individual battery cell voltage (Vcen_max) and bus voltages (Vbus) and output load current, the inductor size can be expressed using the following expression (relative to the duty cycle, DB): _ (nVCett max ^bus^^B (7) ^hfsw Consider a state mismatch scenario where battery cells 1 to 4 have different strengths (i.e. state of charge, or equivalent). In this scenario, according to the voltage sharing principle noted above, different amended duty cycles are assigned to each higher side switch (S1, S3, S5 &S7) to indicate their respective strengths of each battery cell(s). That is, each Buck convertor has a battery cell specific duty cycle applied, called Dit which uses the common indexing ( / ), where / =1 is the case for the first battery cell, being switched by S1 and S2, and / =2 is the case for the second battery cell being switched by switches S3 and S4, etc. This nomenclature will be used throughout the disclosure, (see equation (11) below). This differential approach generates a multi-level voltage across the inductor (Vl) that can reduce the inductor current ripple, analogous to interleaving the Buck converters. The overall output bus voltage (Vbus) can then be expressed as a product of the bus side duty (DB) and sum of all the battery cell voltages (Vceu.) as per the Equation: n ^bus = DB * VcM. (8) i=0 Where DB is now expressed as a sum of all the voltage contributions from all the half bridge Buck converters against the total battery cell voltages, as shown in Equation (9): UB ~ yn tz 2jj=0 Vcelli This can also be approximated as the average of all the duty cycles from each half bridge Buck converter: n DB = (10) n4j i=o Db may then be considered the initial duty cycle that is to be amended according to the below-described further specific examples of the disclosure. It is to be noted that the ideal transition between switches S1 and S2 would occur instantaneously. However, in reality, switching devices (e.g. S1, S2, S3, etc) have rise and fall times, and even the most advanced switches and gate drivers cannot ensure instantaneous switching. Therefore, the higher side switch (S1, S3, etc) and lower side switch (S2, S4, etc) switching may overlap during the transition, generating a short-circuit path for the respective source battery cell, a phenomenon commonly referred to as "shoot-through." Whilst this phenomenon only lasts for a small period of time, the repetitive usage of switched equipment in this manner can shorten their lifespan. Although the impact on the cell may be less of a concern for EOL cells that may be used in some examples, because they are already significantly degraded, these batteries may still be used fora second-life application, so avoiding such damage would be beneficial. Therefore, examples may use a remedy for the issue of shoot-through. This remedy is the incorporation of a small amount of dead time, which introduces a delay between switching intervals to prevent overlapping. For instance, in a half-bridge Buck converter, after the higher side switch turns off, a dead time period is initiated during which the inductor current will circulate through the body diode of the lower side switch before the lower side switch turns on. SOC Function: In some examples a SOC derived function may be used to control the discharging of the battery cells. According to these examples, to split current demand by the Bus voltage controller 420, a set of splitting coefficients (a,) are generated, which scale the current demand to each individual battery cell with respect to its state mismatch against the average states of all the battery cells being discharged. According to the following example, the SOC will be the state being controlled, which in some examples may be calculated using coulomb counting. According to examples, the demanded current, in the form of an amended version of the (initial) bus duty cycle Db can be used to express the respective Buck converter duty cycles as shown in Equation (11): Di = aiDB (11) Where is generated by taking the ratio between the / th battery cell’s SOC (SOQ) and the average SOC of all the battery cells that are being managed, as per equation 12: SO Ci Ui = i--------- n^SOCi (12) The equation 12 above indicates that battery cells with SOC values above the average SOC exhibit a larger at coefficient in comparison to battery cells with SOC values below the average SOC. Hence, by creating a variable demand from each battery cell during discharge, and thereby forcing the SOCs towards the average, state equalisation is achieved. Furthermore, since SOC is bounded within the normalised range [0,1] according to some examples, it follows that all battery cells will ultimately be discharged to 0% SOC by the end of the discharging cycle. This outcome can be ascribed to the fact that the average SOC will also diminish to 0, and hence all battery cells will be operating with the goal of reaching the average SOC of 0. This is assuming that all battery cells are of equal capacity. In real life, the battery cell capacities may not actually be equal. Therefore, in some examples, a battery cell capacity adjustment function may be additionally used, as will now be described. Capacity Function According to some examples, for the disclosed battery cell discharging control method to accommodate battery cells of different capacities the splitting coefficient generation needs to be modified. For example, the capacity can be used as a normalising agent to produce a global SOC variable which is understood by the SOC function and therefore can be used to generate amended splitting coefficients a,, similar to as previously discussed. These are referenced as new, transformed splitting coefficients {ainew). By using the principles discussed above, the / th battery cell capacity can be normalised against the average battery cell capacity, thereby producing a scaling factor to the / th SOC, in order to produce a new scaled SOC, defined as the global SOC parameter (SOCgiobai.): SOCglobalt 1 —yn c -SOC, (13) Equation (13) shows that battery cells of a higher capacity will have their SOC’s scaled up, conversely the lower capacity battery cells will have their SOC’s scaled down. Accordingly, in this example, the global SOC truly reflects the charge delivery capability of each battery cell being discharged, which therefore allow the convergence of SOC regardless of the individual capacity misalignments. With this SOC based adjustment in place, the updated splitting coefficient (a^) function may be expressed as. _ SOCglgbali This function can also be leveraged by the State of Health (SOH) of the battery cells involved. For example, the capacity (CAh.) of a particular battery cell(s) may be defined as a function of its SOH and rated capacity (CAb_RATED) as shown in the following equation: Q / ii — SOH * CAh_RATED (15) This is a useful further amendment of the basic battery discharging control method, when intending to re-use the battery cells for a second life application, since it may serve to improve longevity of the battery cells (and hence of the battery packs / modules formed of the battery cells). Splitting Coefficient Transformation There now follows a discussion of a useful transformation of the splitting coefficients (herein also referenced as the a transformation), as shown in Figure 9, in a simple example using two battery cells. The global SOC as per Equation 13 is dispersed about the average global SOC, so the resulting splitting coefficients are also dispersed about an axis at value of 1, where this axis indicates power sharing distribution, with candidates contributing more power when above this axis and less power when below this axis. This is to say, the coefficients for each of the battery cells is moved relative to the power sharing axis, which is related to the normalisation of the values. To re-iterate, a given battery cell(s) being discharged having a normalized value of 1 indicates that the battery state(s) are normalized to the average value, meaning the control method aims to maintain the average value. States above the average (alpha >1) have a scaled-up alpha value (where alpha can be a,, adjusted according to any of the above adjustments, for example for SOH, Capacity or the like), while states below the average (alpha <1) have a scaled-down alpha value. Therefore, when alpha converges to 1, it implies that the states are equal, indicating that the discharge has finished or the states have converged. Using this knowledge it can be appreciated that if it is possible to spread out these splitting coefficients, such that the stronger cells provide an even greater portion of the load, and the weaker cells contribute an even smaller portion, then the SOC convergence can be better controlled and in particular, accelerated. This concept can be compared to how a spring operates, in that the more it is stretched or compressed, the faster it returns to equilibrium, which in the context of this SOC based function, is the quicker convergence of the states. Meanwhile, the minimum value of the splitting coefficient at is 0, which occurs when any S0CGlobaii value is equal to 0. In this instance, the numerator of the function is 0, hence the value of a, is also zero. Furthermore, when all SOCgiobai. values are equal to each other, and to the average of all S0CGlobau values, the value of the coefficient a, will be 1. Also, cii will have a value greater than 1 if SOCgioba[. is greater than the average of all SOCgiobai. values. Moreover, if SOCGioban is significantly more than the average of all SOCgiobai. values, then the numerator will be significantly greater than the denominator. Nevertheless, the denominator is always positive because SOCgiobai. is between 0 and 1. Hence, a, can only be as large as the ratio of SOCgiobai. to the minimum possible value of the denominator, which occurs when all SOCgiobai. values are 0, with one value of SOCgiobai which is 1. In this instance, the denominator has a value of 1 / n and has a value of n (which is also shown in Figure 13). Therefore, n is the upper limit of <Zi. For a wider distribution of the splitting coefficients, in some examples, the method may be further adapted to move all values of away from 1 in either the positive or negative direction, as depicted in Figure 9A, for the two coefficients. To accomplish this, in an example, a negative offset of -1 is initially applied to effectively shift the axis of power sharing to 0, resulting in all values below 1 becoming negative and all values above 1 becoming positive, as demonstrated in Figure 9B. Following that, a gain factor (k) can be applied to expand the positive values further in the positive direction and the negative values more negatively, as demonstrated in Figure 9C. Finally, in the same example, a positive offset of 1 is subsequently applied to restore all coefficients to the original power-sharing axis of 1 as shown in Figure 9D. As depicted in Figure 9D, taken as a whole, both coefficients have experienced a more pronounced spreading (about the power sharing axis, which is at 1 on the X axis - i.e. the normalised value), as indicated by the measurement marker 902 that highlights the difference in spread in comparison to the spread 901 of the initial values. The resultant transformation (so called “a transformation”) for the newly scaled and transformed coefficients can be represented formally as follows: atnew = k * + ei’ (16) where k is a gain coefficient, and e, is an / th cell involved in the discharging, where e; is a normalised value of 1 or 0, and a value of 0 results in the bypassing of the respective battery cell during a portion of a discharge period, whereas the value of 1 results in the insertion (i.e. inclusion) of the respective battery cell. This may be represented for the normalised situation by the equation: ai-new = * (ai — 1) + 1 (17) Following this transformation, the resulting amended duty cycle D[ on each converter may be expressed as: Di - ainew * (18) SOC Spread Limitation The effectiveness of the proposed method for DC bus voltage management is dependent on the SOC distribution among the battery cells being discharged. Specifically, a large variation in SOC values can inhibit convergence according to the method, and hence the realisation of the target DC output bus voltage Vbus. To address this issue, a larger gain coefficient (k) may be utilised to widen the splitting coefficients to impose a greater demand on the stronger battery cell(s) and lessen the demand on the weaker battery cell(s). In some examples, extremely weak battery cells may be bypassed until they capable of contributing anything to the load. However, excessively high values of k can result in all battery cell(s) with SOC below the average being clamped to a duty cycle of 0, causing the required bus duty cycle (DB) to drop and ultimately lead to failed DC out bus voltage regulation (e.g. there are not enough batteries able to contribute to maintain the desired output voltage). To mitigate this issue, a dynamic clamp can be implemented to constrain the maximum value of k (where the constrained version of k is referred to as kciamp), allowing it to adapt and expand its range as the SOC values converge. For example, where the lower limit for the gain coefficient may be defined as 1, indicating no additional spread in coefficients, the maximum limit may be established based on a function that considers the diversity in SOC levels among the battery cells being discharged. Put another way, the method is arranged to keep discharge under control to ensure convergences of states whilst maintaining the bus voltage Vbus. So, for example, if we have very large dispersion of batteries (i.e. dispersion between strong and weak), if the k value is cranked up, then what happens is the weaker cells get clamped to 0 therefore their duty cycle is 0, and they contribute no energy. Therefore, this clamping reduces the respective amended bus duty cycle which in turn may reduce the bus voltage Vbus and causes failing regulation. Conversely, if the k value is not increase, in a wide state dispersion, the stronger cells may not discharge as fast, ultimately failing state convergence. Thus, a suitable clamped k, kciamp, value may be derived as follows, for example, by using equations (14), (17) and (18) and rearranging them for k while setting the SOC values to 1, a boundary condition can be created as follows: 1 clamp — 7 : n * I {SOC(;iobab} _ - B 11 I x c / Tf (19) Terminal Voltage Function During battery cell discharge, variable discharging currents and incorrect initial SOC selection may cause a mismatch between the terminal voltage and SOC of a particular battery cell. This is due to the varying currents generating a varied voltage drop across the battery cell's internal resistance, which results in a mismatch between the terminal voltages compared to other battery cells being discharged. Additionally, selecting an incorrect initial SOC can cause errors to accumulate (for example due to the coulomb counting integrator), creating a wider difference between the terminal voltage and the estimated SOC. To address this issue, there is also proposed a optional function that can adjust the splitting coefficients to converge the output voltages (of each individual battery cell), which is a basic form of state convergence. This battery cell output voltage based discharging control solution can also be used as a standalone technique within the primary SOC based method, which thereby enables a 'black-box’ solution that eliminates any need for external data battery capacity / state of charge / state of health information, for example, as used for coulomb counting to function. For example, if the voltage profile of a battery cell (lithium-polymer, LiPo, cell in this example) during use ranges from 4.2V (a.k.a. “fully charged”) to 2.5V (a.k.a. “discharged”) and this voltage profile is used to split the load demand, the battery cells will not converge their SOC within a single discharge cycle. This is because the average terminal voltage will always be greater than 0, with a minimum of 2.5V, and will not create a large enough spread in the splitting coefficients to converge in one cycle. Furthermore, if a battery cell reaches its cut off voltage (= 2.5V, for LiPo battery cells) during discharge, it can be bypassed using the inherent fault-tolerant feature of this topology. However, this bypass capability comes at the cost of losing a voltage source contributing to the desired output voltage, which may impact the DC bus voltage delivery capability. To overcome these issues, the maximum and minimum terminal voltages may therefore also be translated into a range of 1 and 0, respectively as shown in Figure 10. Consequently, the translated range value can be normalised against its average value to produce a scaling factor ( / ?,) which can be a weighting to the pre-existing splitting coefficient generation or used on a standalone basis neglecting SOC. To achieve this translation and normalisation process, the higher and lower bounds of the battery cell terminal voltages are defined, which are used to express the terminal voltage on a per unit basis (VT_pui), according to the equation (19): max vmin where VTi is the battery cell terminal voltage, is the higher bound of the battery cell terminal voltage, Vmln is the lower bound of the battery cell terminal voltage, and VT_puis the translated terminal voltage of a respective battery module of the plurality of battery modules being discharged. Therefore the newly generated scaling factor (Pi) can be expressed, for each respective battery cell (i.e. / 1h battery cell) being discharged, in the following way: Pi = VT-put (21) Figure 11 shows a high level diagram of the a transformation 1100, to derive the scaled and transformed splitting coefficients (ai.new) 1120, for use in a battery cell discharging method according to an example of the disclosure, using the equation (16) above. This figure shows how the different control parameters are defined and used, as elaborated upon in the subsequent Figures 12 to 17, and used in the battery cell discharge controller 440 of Figure 4. Figure 11 shows how a set of new scaled and transformed splitting coefficients (ai.new) 1120, are derived from pre-existing initial splitting coefficients (a,) 1105 (which themselves have been previously scaled by scaling factor (Pi), as per Figure 12 and 18, in alternative examples, discussed below). Referring now to the top portion of Figure 11, which relates to the portion handling the first / top battery cell only (and noting this circuitry is basically repeated for each battery cell being discharged), the pre-existing initial splitting coefficients {ap 1105 each have e; subtracted 1110, and the result is multiplied 1112 by an adjusted value of kciamp coming out of a k clamp limiter 1114, and is then upper (u) and lower (I) bounded 1116 by n and -1 respectively. This is done because the method needs to saturate the top end by n due to limits of k and -1, so after transformation, bypassed batteries are limited to a duty cycle of 0 (that is, it operates like an anti windup clamp for integrators). Lastly, the upper and lower bounded values have e; added back in, to form the transformed splitting coefficients (a^new) 1120, which are then used in the circuit of Figure 4, to derive the PWM signals. Figure 12 shows a high level diagram of a first way in which the initial splitting coefficients (ap 1105 may be formed (i.e. a first type of initial splitting coefficients («;)), dependent on the State of Charge and Capacities of the plurality of battery cells. These may form the inputs 1105 to the a transformation 1110 of Figure 11. This shows the way in which the respective battery cell Capacities, CAh. 1210 and average Caave 1220 are combined, and the result then multiplied by the respective battery state of charge values SOCn 1230, to form respective global versions SOCgiobau 1240, that are each compared to a SOC global average SOCgiObai_ave 1250, to which are then applied a set of scaling factors (Pp 1260 to form the first type of initial splitting coefficients (ap 1105. This in effect implements equation (12) to (14) above. There now follows a brief description of a number of different sub-functions providing values used in Figures 11 and 12, as shown in Figures 13 to 17. Figure 13 shows how a value of n is derived, according to an example of the disclosure. In basic terms, the number of cells (n) is computed by aggregating the number of cells requiring discharge (ep. Here, e; is the / 1h cell and the e, values have a binary value of 1 or 0, thereby allowing any given battery cell to be inserted if the respective value of ef is set to 1, or bypassed by setting its value to 0 (the action of which accordingly adjusts the average values). The resulting duty cycle is 0 when e; is 0, thus activating the lower side switch and allowing the discharging operation to continue while the cell is removed (i.e. bypassed) from operation. Figure 14 shows a SOC averaging function, according to an example of the disclosure. In the example shown, this simply calculates the average global SOC value (SOCfliObai_ave), based on n and the sum of all the S0Cgioban values involved. Other averaging methods may also be used instead. Figure 15 shows a battery cell capacity averaging function, according to an example of the disclosure. In the example shown, this simply calculates the average battery cell capacity (Caave), based on n and the sum of all the individual battery cell capacities involved, CAh Other averaging methods may also be used instead. Reverting back to Figure 12, the generated values for the battery cell global SOC (SOCgiobaip and battery cell capacities (CAhf) are then scaled using an alternative set of scaling factors pit for example to account for terminal voltage differences, in which case the values for Pt may be obtained using a terminal voltage function as depicted in Figure 16. These values may undergo a transformation stage, which spreads out the splitting coefficients by applying a gain k (see Figure 9A-9D and associated description, above). The gain k may be limited by dynamic clamp, which sets its upper value as shown in Figure 17, and in effect implements equation 19 noted above. In this transformation, the splitting coefficients are first negatively offset, and then the gain is applied, after which they are positively offset. These offsets are performed using ef (i.e. a value of 1 or 0, with Figure 17 showing when et is - 1) which is the number of battery cells needing discharge, as noted above. As noted above, the battery cell terminal voltage function can be used as a standalone technique to manage the battery cells during discharging without requiring capacity / SOC information. This alternative battery cell terminal voltage function based approach utilises weighting values Pi calculated in a different way to perform the duty cycle D{ scaling, in order to distribute the load current amongst the battery cells being discharged, with respect to the voltage spread, as shown in Figure 18. Furthermore, for this alternative approach, the dynamic clamp function restricting k (to provide kclamp) is updated and calculated instead using the per unit terminal voltages as shown in Figure 19, which in effect implements the equation: 1 1 i, <___ cl amp — / \ / \ I max {VT_pul} \ max {VT_pul} \ UB * I 1 1 I I 1 1 I Thus, it can be seen that the functions shown in Figure 18 and 19 together provide an alternative front end (compared to that of Figure 12) for the function shown in Figure 11, and which provides a second type of initial splitting coefficients (aj 1105, this time dependent on the Voltage thresholds only. Examples of the microcontroller that controls the battery cells discharging process according to the present disclosure may be implemented by suitably programmed computer hardware, for example as shown in Figure 20. Figure 20 is a block diagram 2000 illustrating components, according to some example embodiments, able to read instructions from a machine-readable or computer-readable medium (e.g., a non-transitory machine-readable storage medium) and perform any one or more of the methodologies discussed herein, hence providing the apparatus or system to carry out the described battery cell discharge methods. Specifically, Figure 20 shows a diagrammatic representation of hardware resources 2005 including one or more processors (or processor cores) 2010, one or more memory / storage devices 2020, and one or more communication resources 2030, each of which may be communicatively coupled via a bus 2040. The processors 2010 (e.g., a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a digital signal processor (DSP) such as a baseband processor, an application specific integrated circuit (ASIC), a cloud processing function (such as an AWS instance), another processor, or any suitable combination thereof) may include, for example, a processor 2012 and a processor 2014. The memory / storage devices 2020 may include main memory, disk storage, or any suitable combination thereof. The memory / storage devices 2020 may include, but are not limited to any type of volatile or non-volatile memory such as dynamic random access memory (DRAM), static random-access memory (SRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), Flash memory, solid-state storage device (SSD), magnetic storage based hard disk drive (HDD) media, etc. The communication resources 2030 may include interconnection or network interface components or other suitable devices to communicate with one or more peripheral devices 2004 or one or more databases 2006 via a network 2008. For example, the communication resources 2030 may include wired communication components (e.g., for coupling via Ethernet, a Universal Serial Bus (USB) or the like), cellular communication components, NFC components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components. Instructions 2050 may comprise software, a program, an application, an applet, an app, or other executable code for causing at least any of the processors 2010 to perform any one or more of the methodologies discussed herein. The instructions 2050 may reside, completely or partially, within at least one of the processors 2010 (e.g., within the processor’s cache memory), the memory / storage devices 2020, or any suitable combination thereof. Furthermore, any portion of the instructions 2050 may be transferred to the hardware resources 2005 from any combination of the peripheral devices 2004 or the databases 2006. Accordingly, the memory of processors 2010, the memory / storage devices 2020, the peripheral devices 2004, and the databases 2006 are examples of computer-readable and machine-readable media. In some embodiments, the electronic device(s), network(s), system(s), chip(s) or component(s), or portions or implementations thereof, of Figures 20, or some other figure herein may be configured to perform one or more processes, techniques, or methods as described herein, or portions thereof. In the foregoing, functions are described as modules or blocks, i.e. functional units that are operable to carry out the described function, algorithm, or the like. These terms may be interchangeable. Where modules, blocks, or functional units have been described, they may be formed as processing circuitry, where the circuitry may be general purpose processor circuitry configured by program code to perform specified processing functions. The circuitry may also be configured by modification to the processing hardware. Configuration of the circuitry to perform a specified functions may be entirely in hardware, entirely in software or using a combination of hardware modification and software execution. Program instructions may be used to configure logic gates of general purpose or special-purpose processor circuitry to perform a processing function. Circuitry may be implemented, for example, as a hardware circuit comprising custom Very Large Scale Integrated, VLSI, circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. Circuitry may also be implemented in programmable hardware devices such as field programmable gate arrays, FPGA, programmable array logic, programmable logic devices, A System on Chip, SoC, or the like. Machine readable program instructions may be provided on a transitory medium such as a transmission medium or on a non-transitory medium such as a storage medium. Such machine readable instructions (computer program code) may be implemented in a high level procedural or object oriented programming language. However, the program(s) may be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language, and combined with hardware implementations. Program instructions may be executed on a single processor or on two or more processors in a distributed manner. Examples provide a method of controlling discharging of a plurality of battery modules through a plurality of power convertors, each power converter connected across a particular battery module of the plurality of battery modules, the method comprising: determining a first, initial, plurality of splitting coefficients, ab for the plurality of battery modules, wherein a splitting coefficient associated with a particular battery module determines a proportion of an output power produced during discharging contributed by the particular battery module; determining a scaling factor, for each battery module, for scaling the first plurality of splitting coefficients, ab scaling each of the first plurality of splitting coefficients, ab by the respective scaling factor, Pi to form a scaled first plurality of splitting coefficients; transforming the scaled first plurality of splitting coefficients to form a second, new, plurality of transformed splitting coefficients, ainew, wherein the transformation comprises spreading out the transformed splitting coefficients compared to the initial splitting coefficients, such that weaker ones of the plurality of battery modules contribute less power to a load, and stronger battery modules of the plurality of battery modules contribute more power to the load; and controlling the plurality of power converters to provide an output voltage using a plurality of pulse width modulated, PWM, signals, determined using an adjusted duty cycle, Db based on the second plurality of transformed splitting coefficients, «tnew and an initial bus duty cycle DB, In some examples, D< = a,- D,, L Lnew & In some examples, a battery module is a battery cell. Spreading out the splitting coefficients comprises may comprise stretching out, or extending, a distance between the coefficients on a normalised power sharing axis In some examples, transforming the scaled first plurality of splitting coefficients to form a second, new, plurality of transformed splitting coefficients operates according to the equation: aL = k*(a< — e.) + e;; Lnew v i iz i' wherein k is a predetermined gain coefficient; and wherein e; is an / 1h battery module involved in the discharging, and wherein an e; value of 0 results in bypassing of a respective battery module during a portion of a discharge period, and a e, value of 1 results in the insertion of the respective battery module during a portion of a discharge period to thereby provide energy during discharge. In some examples, et is a normalised value. In some examples, each scaling factor, is determined by: determining a maximum and minimum terminal voltage of each of the plurality of battery modules coupled to a respective power convertor; translating the maximum and minimum terminal voltages of each of the plurality of battery modules coupled to a respective power convertor into the range between 1 and 0; and normalising the translated maximum and minimum input voltages against an average input voltage value. In some examples, the maximum and minimum terminal voltages of each of the plurality of battery modules are dependent on a specific battery module arrangement being used, and / or battery chemistry. In some examples, translating and normalising of the maximum and minimum terminal voltages of each ofthe plurality of battery modules is derived from a higher and lower bound of the battery module terminal voltage. In some examples, translating and normalising ofthe maximum and minimum terminal voltages of each ofthe plurality of battery modules comprises applying the equation: v_. - y . ,, _ vTi vmin T~Put “ y _ y . vmax v min wherein VTi is the terminal voltage of a battery module of the plurality of battery modules; Vp-puts the translated terminal voltage of a battery module of the plurality of battery modules; Vmax is the higher bound of the battery module terminal voltage, and Vmin is the lower bound of the battery module terminal voltage. In some examples, the scaling factor for each battery module of the plurality of battery modules is determined by dividing the translated terminal voltage of a respective battery module of the plurality of battery modules by the average translated terminal voltage of the plurality of battery modules. In some examples, the dividing comprises applying the equation: ~ v T-put wherein n is the number of battery modules In some examples, the gain coefficient, k, is clamped, and derived from the equation: 1 1 k 1 <---------7-------------------------v---7------------------------- lvclamp — / \ / / max{VT nj, / l \ / max i t i putj ill ' puu * I 1 I 1 1 wherein SfL I ^T-pui is an averaging function to determine an average battery module terminal voltage value. In some examples, the first, initial, plurality of splitting coefficients, ait for the plurality of battery modules may be determined from an initial state of charge of each battery module of the plurality of battery modules before discharging begins. In some examples, the first, initial, plurality of splitting coefficients, at are derived from the equation: SO Ct - ^iSOCt Some examples further comprise normalising the initial state of charge of each battery module according to a determined average capacity of all battery modules being discharged. In some examples, wherein normalising the initial state of charge of each battery module comprises applying the equation: CAh. SOCglobali=-------*SOCt — vn c ^Aht and substituting the values SOCglobal. for the values of SOCt into the equation _ SOCt In some examples, CAh. for each battery module of the plurality of battery modules comprises a nominal battery module capacity, or is derived from a rated battery module capacity adjusted by a State of Health of the battery module according to the equation: ^Ahi = SOH * CAh_RATED In some examples, the gain coefficient, k, is clamped, and derived from the equation: 1 1 If ________ db * wherein ^£i=1SOCGiobait is an averaging function to determine an average global SOC value. In some examples, the averaging function uses a number of battery modules value, n, wherein n is calculated by aggregating each battery module requiring discharge, e£ and accordingly adjust an output value of the averaging function. max{SOCg£ol,a£.} 1 ' —yn soc , .. , ^^^globali In some examples, the initial duty cycle, DB, is an output of the a closed loop controller. In some examples, the closed loop controller is a Proportional Integral, PID, or any other closed loop controller. In some examples, the initial duty cycle, DB, is calculated from a desired output voltage, Vbus, a sampled value for the voltage bus at a point in time, Vbus-sense, and a sampled value for the current at the point in time, lsense. Examples also provide a method of discharging a plurality of battery modules (e.g. for onward deconstructive recycling) by determining a number of splitting variables that provide a variable demand for discharge energy from each battery modules during discharge, and then applying said variable splitting variables, to thereby force an equal discharging overtime, such that an end result of the discharging process is the full discharge of all battery modules involved in the discharging process. The forced equal discharge may be provided by determining the splitting variables from one or more predetermined battery parameter(s) of each of the battery modules, for example, by forcing the discharge of the battery modules such that the one or more predetermined battery parameter(s) for each module tends towards an average value (e.g. the average of all battery modules). The predetermined battery parameter(s) used may be derived from State of Charge, battery terminal voltages, or any of the other specific, and independently applicable assessments of the battery involved in the discharging process, as disclosed herein. Examples also provide a method of discharging a plurality of battery cells (or modules) that make use of determining a number of splitting coefficients that provides a variable demand from each battery cell during discharge, to thereby force SOCs towards an average value (e.g. the average of all battery cells), to thereby force an equal end result of the discharging process, wherein the end result is the full discharge of all battery cells involved in the discharging process. Examples also provide a computer program product or computer readable medium, comprising instructions, which, when carried out by one or more processors cause the one or more processors to carry out any of the disclosed discharge methods. The one or more processes may operate in response to one or more inputs form sensors detecting parameters of the plurality of battery modules to be, or being, discharged. Examples also provide any form of apparatus that is arranged to carry out any of the disclosed methods, or portions thereof. Examples of such an apparatus may further comprise: a plurality of DC-DC converters; and a global filter, for example, comprising a global inductive entity (e.g. Lo220) and a global capacitive entity (e.g. Co 240). Examples may further comprise a suitable programmed controller, such as microcontroller, configured to (i.e. operative to) carry out the disclosed discharging method(s), for example using the plurality of DC-DC converters. Each one of the plurality of DC-DC converters may be coupled to a respective battery cell / module to be discharged. The plurality of DC-DC convertors may be Buck converters. Examples also provide a battery discharge and energy re-use system comprising any of the disclosed battery discharging apparatus(es), and an invertor arrangement to re-use the energy extracted from a plurality of battery modules to be discharged. Note, in the foregoing equations, including subscripts (and the equivalents in the associated drawings), n, n, i and i may have been used interchangeably, and is meant to refer to the / th instance of an associated value, variable, equation or similar, associated with the / th battery module out of n battery modules involved. While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the scope of the disclosure. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in any combination in practicing the disclosure. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.

Claims

1. A method of controlling discharging of a plurality of battery modules through a plurality of power convertors, each power converter connected across a particular battery module of the plurality of battery modules, the method comprising:determining a first, initial, plurality of splitting coefficients, ait for the plurality of battery modules, wherein a splitting coefficient associated with a particular battery module determines a proportion of an output power produced during discharging contributed by the particular battery module;determining a scaling factor, for each battery module, for scaling the first plurality of splitting coefficients,scaling each of the first plurality of splitting coefficients, a^, by the respective scaling factor, to form a scaled first plurality of splitting coefficients;transforming the scaled first plurality of splitting coefficients to form a second, new, plurality of transformed splitting coefficients, ainew, wherein the transformation comprises spreading out the transformed splitting coefficients compared to the initial splitting coefficients, such that weaker ones of the plurality of battery modules contribute less power to a load, and stronger battery modules of the plurality of battery modules contribute more power to the load; andcontrolling the plurality of power converters to provide an output voltage using a plurality of pulse width modulated, PWM, signals, determined using an adjusted duty cycle, D{ based on the second plurality of transformed splittingcoefficients, ainew and an initial bus duty cycle DB2. The method of claim 1, wherein:D / = a, DB 1 hiew &3. The method of claim 1 or 2, wherein transforming the scaled first plurality of splitting coefficients to form a second, new, plurality of transformed splitting coefficients operates according to the equation:a, = k* (a, - e<) + e,-; ‘new x 1 1wherein k is a predetermined gain coefficient; andwherein e; is an / th battery module involved in the discharging, and wherein an e, value of 0 results in bypassing of a respective battery module during a portion of a discharge period, and a e; value of 1 results in the insertion of the respective battery module during a portion of a discharge period to thereby provide energy during discharge.

4. The method of claim 1, wherein each scaling factor, pi, is determined by:determining a maximum and minimum terminal voltage of each of the plurality of battery modules coupled to a respective power convertor;translating the maximum and minimum terminal voltages of each of the plurality of battery modules coupled to a respective power convertor into the range between 1 and 0; andnormalising the translated maximum and minimum input voltages against an average input voltage value.

5. The method of claim 4, wherein translating and normalising of the maximum and minimum terminal voltages of each of the plurality of battery modules is derived from a higher and lower bound of the battery module terminal voltage.

6. The method of claim 5, wherein translating and normalising of the maximum and minimum terminal voltages of each of the plurality of battery modules comprises applying the equation:,, _ ^minT~Pui “ y _ y . vmax v minwherein VTi is the terminal voltage of a battery module of the plurality of battery modules;VT^pu. is the translated terminal voltage of a battery module of the plurality of battery modules;Vmax is the higher bound of the battery module terminal voltage, andVmin is the lower bound of the battery module terminal voltage.

7. The method of claim 6, wherein the scaling factor for each battery module of the plurality of battery modules is determined by dividing the translated terminal voltage of a respective battery module of the plurality of battery modules by the average translated terminal voltage of the plurality of battery modules.

8. The method of any of claims 3 to 7, wherein the gain coefficient, k, is clamped, and derived from the equation:1 1 Is ___________________________________________________ __ _________________________________________— / \ / \max {VT_pul} \ max {VT_pul} \UB * I 1 1 I I 1 1 IY^iVr-pui / \^"=1^-pu£ / wherein ^S”=i Vr^putis an averaging function to determine an average battery module terminal voltage value.

9. The method of any of claims 1 to 3, wherein the first, initial, plurality of splitting coefficients, for the plurality of battery modules is determined from an initial state of charge of each battery module of the plurality of battery modules before discharging begins.

10. The method of claim 9, wherein the first, initial, plurality of splitting coefficients, are derived from the equation:soc. al — 1 ^"=1 SOCi11. The method of claim 9 or 10, further comprising normalising the initial state of charge of each battery module according to a determined average capacity of all battery modules being discharged.

12. The method of claim 11, wherein normalising the initial state of charge of each battery module comprises applying the equation:CAh.SOCglobah = ---*SOCt—V" c71^1=1 JAh:and substituting the values SOCgiobai. for the values of SOC, into the equation of claim 10.

13. The method of claim 12, wherein CAh. for each battery module of the plurality of battery modules comprises a nominal battery module capacity, or is derived from a rated battery module capacity adjusted by a State of Health of the battery module according to the equation:Cam — SOH * CAh^RATED14. The method of any of claims 1 to 3 or 9 to 13, wherein the gain coefficient, k, is clamped, and derived from the equation:1 1k , <----------------------------------?---r—^clamp — / \ / \ / max{SOCflioba„} \ / max{S0Caio6aiJ \Dp * -------—---- — 1 -------—---- — 1\Ayn cQr / \Ayn cnr , / / Zji=i ^^^globali / wherein ^SP=1SOCgiO6a(i is an averaging function to determine an average global SOC value.

15. The method of any of claims 9 to 14, wherein the averaging function uses a number of battery modules value, n, wherein n is calculated by aggregating each battery module requiring discharge, e{.

16. The method of any preceding claim, wherein the initial duty cycle, DB, is an output of the a closed loop controller.

17. The method of claim 16, wherein the closed loop controller is a Proportional Integral controller.

18. The method of any preceding claim, wherein initial duty cycle, DB, is calculated from a desired output voltage, Vbus, a sampled value for the voltage bus at a point in time, Vbus-sense, and a sampled value for the current at the point in time, I sense-19. An apparatus arranged to carry out the method of any of claims 1 to 18.

20. The apparatus of claim 19, further comprising:a plurality of DC-DC converters;a global inductive entity; anda global capacitive entity.

21. A battery discharge and energy re-use system comprising the apparatus of claim 19 or 20, and an invertor arrangement to re-use the energy extracted from a plurality of battery modules to be discharged.

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