Method and arrangement for charging / discharging a high-voltage battery system

Description

[0001] The invention relates to a method for controlling the charge / discharge of a high-voltage battery system according to the preamble of claim 1 and to an arrangement for carrying out the method according to the preamble of claim 7. The invention is particularly applicable in a purely battery-operated vehicle or a partially battery-operated vehicle, in particular a plug-in hybrid vehicle.

[0002] High-voltage battery systems are used to store energy for many purposes, particularly where off-grid operation is necessary or desired. Such energy storage devices can be found, for example, in cars, ships, and aircraft, where they supply the energy needed to start the engine. In recent years, their use as traction batteries for partially or fully electric vehicles has gained enormous importance. Small electrically operated devices, such as power tools, smartphones, and cameras, are also powered by accumulators—i.e., rechargeable batteries. Furthermore, rechargeable energy storage devices of the type in question here are becoming increasingly important as buffer storage devices for initially storing wind or solar energy and feeding it into the power grid at a later time.

[0003] Depending on the application, different types of batteries are used, differing primarily in the materials used for energy storage. Lead-acid batteries, for example, are commonly used as starter batteries for cars. Portable electrical or electronic devices typically use lithium-ion batteries. Lithium-based energy storage devices are also commonly found in partially or fully electric vehicles.

[0004] All known types of rechargeable batteries have one thing in common: they are subject to aging. A key factor in the aging of rechargeable energy storage devices of this type, in addition to the temperature at which the storage device is exposed, is the voltage range within which it is operated. Regarding temperature, in large-scale applications (buffer storage) or in vehicles as traction batteries, precautions are usually taken to ensure that the temperature does not fall below or rise above a specified level. Regarding the voltage range within which the battery is operated, both overcharging (high voltage) and overdischarging (low voltage) can significantly reduce its service life. Manufacturers therefore usually specify a permissible state of charge (SoC) range.The "state of charge" (SOC) specifies the range within which the battery must be operated to achieve a guaranteed number of cycles or a guaranteed aging period. The permissible SOC range varies depending on the battery type. For lithium-ion batteries, for example, the middle charge range between 10% and 80% is used, while for lead-acid batteries, the upper charge range between 60% and 100% is used.

[0005] As can be seen from the above, particularly when using high-voltage battery systems, there is often a conflict of objectives between the desire to minimize aging of the energy storage device and the requirement to keep the energy storage device as small as possible for cost reasons. This is the case, for example, with traction batteries in electric or partially electric vehicles, because an aging-optimized restriction of the state of charge range by introducing a correspondingly narrowed SoC window, i.e. the range permitted for the use of the charge through appropriate control of the charging or discharging process, has a direct impact on the achievable range. This conflict of objectives of keeping the battery as small as possible while minimizing aging as much as possible also exists in other applications of high-voltage battery systems.

[0006] To address the problem of aging, attempts have so far been made to compromise on larger high-voltage battery systems, accepting a higher price. This meant using high-voltage batteries with a higher gross capacity and operating them within a fixed SoC window within an aging-optimized range. A correspondingly lower net capacity was accepted in this process.

[0007] Such a static restriction of the net capacity proves to be highly restrictive in many cases, for example, in the real-life operation of electric-powered passenger vehicles. In order to operate such vehicles as flexibly as possible, US Pat. No. 8,970,173 B2 proposes a method for setting the operating mode of an electric vehicle, wherein the operating mode is selected from a plurality of operating modes. The plurality of operating modes comprises at least one battery life mode and a standard mode, wherein the battery life mode is configured with respect to the selection of operating and charging parameters such that the battery condition and battery life are emphasized over the vehicle range and / or vehicle performance.The system includes a thermal management system for maintaining the vehicle's battery pack within one of several temperature ranges and a charging system for charging the vehicle's battery pack to one of several minimum and maximum SoC levels. Thus, SoC windows adapted to several predefined operating modes are maintained and set by the driver using a selector. While such a choice provides greater flexibility in vehicle use, it places the responsibility for maximizing the high-voltage battery's service life on the driver.

[0008] Another approach is proposed in EP 3 050 739 A1. The method described therein provides that for the control and / or regulation of at least one operating parameter of the electrical energy storage device influencing an aging state of an electrical energy storage device of a motor vehicle, an actual aging state of the electrical energy storage device and a target aging state are determined. By comparing the actual aging state with the target aging state, it is determined whether the actual aging state shows increased aging compared to the target aging state or lesser aging. If the actual aging state is increased compared to the target aging state, an operating parameter range is adjusted such that the electrical energy storage device operates within the adjusted operating parameter range at a reduced aging rate.If the actual aging state is lower than the target aging state, the operating parameter range can be adjusted such that the electrical energy storage device operates at an increased aging rate within the adjusted operating parameter range. According to one embodiment, the adjusted operating parameter range can be the state of charge (SoC) window of the energy storage device.

[0009] While this approach enables aging-optimized operation of an energy storage device, determining the actual aging state of the energy storage device is complex and imprecise. Furthermore, it ignores the fact that in many operating cases, the charge required for operation between two charging processes is much lower than the SoC window specified by the actual aging state.

[0010] WO 2013 / 055830 A1 discloses a generic method and a generic arrangement. US 2011 / 202217 A1 discloses electric vehicle equipment for grid-integrated vehicles. EP 2 502 774 A1 discloses a vehicle and a control method for the vehicle. EP 2 662 949 A1 discloses a charging control device, a charging control method, and a program therefor. US 2020 / 108726 A1 discloses a variable charging strategy for plug-in electric vehicles.

[0011] The object of the invention is to provide a method in which the SoC window is dynamically determined such that the charge actually required between two charging processes is available. The actually required charge is understood to be the charge that is necessary—possibly including a safety reserve—to accomplish a task to be performed using the stored charge. Furthermore, the object is to specify a system for implementing the method.

[0012] The object is achieved by the features of claim 1 or 7. Preferred developments of the invention are disclosed in the subclaims.

[0013] The starting point is an implemented charge / discharge control of a high-voltage battery system, which allows to set different state of charge ranges by introducing correspondingly narrowed SoC windows to optimize the aging of the battery.

[0014] In real-life operation of high-voltage battery systems, it has been found that in the majority of cases only a very small portion of the net capacity is used up between two charging options, although this actually required capacity can be subject to considerable fluctuations. Based on this consideration, it was found that for a large number of application cases, the actually required capacity can be predictively estimated by taking into account a series of parameters. To solve this problem, a method is therefore proposed in which at least one parameter is determined in a process preceding a charging process that predicts the usable capacity of the battery required until the next charging process. The at least one parameter is then converted into a required usable capacity, and from this, an SoC window is determined that optimizes the aging state of the battery.Optimizing the battery's aging state here means that the SoC window is, in many cases, smaller than the maximum permissible SoC window (SoC-F max) and lies within the maximum permissible SoC window (SoC-F max ). The SoC window is set using the charge / discharge control, and the battery is charged within the range specified by the SoC window. During operation, the charge / discharge control controls the discharge of the battery so that the state of charge remains within the state of charge range specified by the SoC window.

[0015] The advantage of the method according to the invention is that the lower value of the SoC window UG (SoC-F) and the upper value of the SoC window OG (SoC-F) are dynamically set to values ​​that cover the actually required capacity of the battery through predictive estimation of the capacity required between two charging processes. This results in the majority of cases, due to a required capacity that is less than the permissible net capacity, the lower value of the target SoC window is set larger than the minimum permissible lower value of the maximum permissible SoC window and the upper value of the target SoC window is set smaller than the maximum permissible upper value of the maximum permissible SoC window. Thus, in these cases, the battery is operated in a range that is favorable for aging.The actual aging of the battery thus always remains smaller than the aging that occurs when the SoC window is set to the maximum permissible net capacity specified by the manufacturer. The method according to the invention automatically guides battery aging to an optimum without the need for external intervention and without compromising comfort.

[0016] Since predictive estimates of the amount of energy required to complete a task are always subject to uncertainty, it can be advantageous to provide that the usable capacity forecast until the next recharge includes a safety reserve.

[0017] In an embodiment of the method according to the invention, it can be advantageous that, in the event that the required usable capacity is greater than the maximum permissible net capacity of the battery specified by the manufacturer, the charge / discharge controller checks whether the SoC window for a specified number of charge / discharge cycles was smaller than the maximum permissible SoC window. If this is the case, the charge / discharge controller sets an SoC window that is larger than the maximum permissible SoC window and less than or equal to a predefined extended SoC window. This procedure allows, in exceptional cases, the battery to be charged to an extended net capacity that is greater than the maximum permissible net capacity specified by the manufacturer.

[0018] In cases where the determined required usable capacity is greater than the maximum permissible net capacity of the battery specified by the manufacturer and / or greater than the extended net capacity, it can be advantageous for the charge / discharge control to trigger a signal. The signal can be visual, acoustic, or haptic. This signals an operator that a predefined task can only be completed with an intermediate charge.

[0019] The at least one parameter determined in the process upstream of charging, which predicts the usable capacity of the battery required until the next charge, can be of a different nature. For example, it is possible to use a predefined task as a parameter. For example, it can be provided to select a predefined task from a plurality of predefined tasks and use the parameter assigned to it. According to the invention, a task is predicted. To obtain a parameter, a plurality of parameters for determining the task can be used.For example, if a task requires a fully electric vehicle to travel a specific distance between location "A" and location "B," the distance to be covered and an associated elevation profile can be determined as parameters from the route determined using a route calculation system. From these parameters, a first characteristic can be formed, which at least partially defines the task with regard to the energy required to complete it. One characteristic according to the invention is ambient conditions. According to the invention, at least the outside temperature is used as a parameter for ambient conditions. Additional considerations include the season, the time of day, or other environmental parameters from which a characteristic can be formed, such as the traffic situation at a specific time of day.With regard to the exemplary task of completing a route "A - B," this means that a second parameter is generated from, for example, the temperature prevailing at a certain time of year and the traffic situation prevailing at a certain time of day. Another parameter can be of a personal nature, namely when the characteristics of an operator play a role in completing a task with regard to the energy required. In such a case, a personal behavior analysis conducted in advance can determine, for example, an increased or reduced energy consumption as a parameter. In relation to the example chosen here, "completing a certain route," this means that, for example, a driving style analysis conducted in advance provides an energy consumption-specific parameter.

[0020] An essential aspect of the invention is that each charging process can be controlled depending, among other things, on the outside temperatures and the resulting air conditioning requirements in such a way that the driver is always provided with a reliable fixed / constant range, in particular over the entire guaranteed service life of the high-voltage traction battery.

[0021] The parameters determined in the above example "Coping with a certain distance", when calculated accordingly, together result in a predicted necessary battery capacity, which must be maintained by charging the battery accordingly to cover the distance.

[0022] As the example chosen above already shows, the method according to the invention is particularly advantageous for use in conjunction with a high-voltage traction battery of a fully or partially electric vehicle. In a particularly simple variant, it can advantageously be provided that the predefined task is to cover a minimum distance with a predefined elevation profile, whereby the length of the route (e.g., 50 km, 100 km, 150 km, etc.) as well as the elevation profile (e.g., "flat," "hilly," "mountainous") can be entered via appropriate input means. The input is converted into a parameter that defines the battery capacity required to complete the task, for example, a 100 km distance with a "flat" elevation profile.

[0023] Following a route determined in advance offers the significant advantage that intervention by the vehicle operator is not necessary. According to the invention, a route calculation system is used to determine the route. This system advantageously uses data from a planning system, whereby the planning system can be an electronic appointment calendar, an electronic dispatch planner for a goods distribution system, or similar devices in which the locations to be visited, the sequence of the locations to be visited, and / or the time of day at which arrival at at least one location is planned are stored. In this way, the route calculation system can determine a route and determine the characteristic value from the determined route and the elevation profile assigned to the route, or an equivalent value.

[0024] The outside temperature is also important for the energy consumption of a fully or partially electric vehicle. Therefore, according to the invention, the outside temperature is taken from a memory in which a plurality of outside temperatures are stored predefined by season, time of day, and / or location. According to the invention, the respective applicable outside temperature is taken from the memory using at least one date, time, and / or location and forms a characteristic value.

[0025] Another advantageous way of obtaining the outside temperature is to obtain outside temperatures defined in time and / or place as forecast outside temperatures from a weather forecast system, for example by means of radio data transmission.

[0026] According to the invention, a plurality of forecast outside temperatures are determined from a weather forecast system in relation to location and / or time for a determined route, and the outside temperatures thus obtained are linked to the route in relation to location and time, whereby the expected characteristic and / or the required capacity of the battery is determined from these linked data.

[0027] In order to also incorporate the specific characteristics of a vehicle driver into the determination of the predictively estimated, i.e., the expected required capacity to perform the task, the invention provides for determining the individual's additional or reduced energy consumption in a preliminary individual consumption analysis and generating a parameter from this. In this way, the expected required battery capacity can be determined using the driving route as the first parameter, the predicted outside temperatures as the second parameter, and the third driver-specific parameter.

[0028] If a tool, vehicle, or system powered by a high-voltage battery system is used in essentially the same way every time, it may be sufficient to obtain at least one characteristic from the evaluation of at least one previous charge / discharge cycle. For example, before the first use, the battery can be charged to its net capacity. During the first use, the actually required capacity is recorded and used as a characteristic to determine the capacity required for the next use, derive an SoC window from it, and charge the battery within the limits specified by the SoC window for the next use.

[0029] In addition to the method mentioned above, the invention also includes a charging / discharging arrangement for carrying out the method. The charging / discharging arrangement advantageously contains a number of components, which are discussed below.

[0030] For a better understanding of the following explanations, it should be noted in advance that the charging / discharging arrangement in question is an arrangement of mechanical and electronic components, as are commonly used today. Such charging / discharging arrangements are usually part of a computer-aided control system that uses processors to process control instructions stored in memories. In particular, the components discussed below and the control sequences they execute are control instructions summarized in command routines which – processed by the processor(s) – execute the control tasks assigned to them using input and output devices, sensors, actuators, and transmission devices operatively connected to the processor(s).The components discussed below are therefore normally not definable hardware units but exist only virtually and temporarily within a computer-aided control system.

[0031] The charging / discharging arrangement contains a determination device that determines at least one characteristic, wherein the characteristic predicts the usable capacity of the battery required until the next charge. As shown above, the determination device can obtain data from subsystems with which it is temporarily connected, for example by radio, via a corresponding data exchange. In order to arrive at a usable capacity required to perform a task from the characteristic or characteristics, a calculation device is provided that determines a required usable capacity or an equivalent value from the characteristic or characteristics. The method by which this is done can vary: For example, the characteristics can be used to determine the required usable capacity from a characteristic curve or a characteristic map.However, it may also be necessary to perform complex calculations, depending on the nature of the parameters. Furthermore, a determination device is provided which determines an SoC window that optimizes the aging state of the battery from the required usable capacity. To do this, the determination device uses a simple assignment rule. Furthermore, a setting device is provided which sets the lower value of the SoC window and the upper value of the SoC window. Finally, the charging / discharging arrangement is designed such that it controls the charging process such that the battery is charged up to the upper value of the SoC window and controls the discharging process during operation such that the battery is only discharged down to the lower value of the SoC window. The components mentioned above can be part of a global control system that takes over the control of the vehicle as a whole.It is particularly advantageous to design the charging / discharging arrangement as a module that can be optionally added to the control system.

[0032] Further embodiments and advantages of the invention are explained in more detail below with reference to the drawings. They show: Fig. 1 shows a simplified functional block diagram of an arrangement for charging / discharging a high-voltage battery system; Fig. 2 shows a simplified representation of the required capacity of a traction battery of a vehicle, depending on the distance traveled and the type of terrain profile, in the form of a characteristic map; Fig. 3 shows a representation of the relationship between capacity and SoC window in a high-voltage battery system; Fig. 4 shows a flowchart for an exemplary method sequence; and Figs. 5 to 9 each show further exemplary embodiments of the invention.

[0033] In the representation according to Fig. 1is shown in a simplified functional block diagram of an arrangement for charging / discharging a high-voltage battery system 5. The example described below assumes that the charging / discharging control arrangement 1 is part of a fully electric vehicle (not shown here). Regarding the representation in the form of functional blocks, it should be noted that these are not normally definable hardware units, but rather exist only virtually and temporarily within the framework of a computer-aided control system. Computer-aided control systems of this type are common in automotive engineering. They process control instructions stored in memories using processors.In particular, the components (function blocks) addressed below and the control sequences they execute are control instructions combined into command routines which - processed by the processor(s) - execute the control tasks assigned to them by means of input or output means, sensors, actuators and transmission means that are operatively connected to the processor(s).

[0034] The charging / discharging control arrangement 1 contains a determination device 2. This is initiated by plugging a charging plug 3 into a charging station 4 to determine parameters. The determined parameters predict the usable capacity of a high-voltage battery system 5 required until the next charging, in other words, the energy requirement that must be maintained in the battery 5 to complete a task until the next charging. In the selected example, it is provided that the task to be completed is determined by the determination device 2 from an electronic appointment calendar 6. It is further assumed that the locations to be visited by the vehicle and the order in which they are to be visited are stored in the electronic appointment calendar 6 in a way that is identifiable for the determination device 2.

[0035] For example, it is assumed that the appointment calendar entries indicate that at a given time "X", starting from the current position at charging station 4, three locations are to be visited in the order "A", "B", "C", and then charging station 4, and that the journey ends at a time "Y". Charging station 4 can, for example, be a wall box at the vehicle's home location. To determine the task that needs to be completed before the next charging process, determination device 2 transfers the task definition charging station 4 -> location "A" -> location "B" -> location "C" -> charging station 4 to a route calculation system 7, which can be part of a navigation system (not shown here), in order to determine a driving route.It is assumed here that the route calculation system 7 determines a route from the data transmitted to it, which, in addition to the route, which is not relevant in this context, determines the desired distance S and the terrain profile (elevation profile) GP and transmits this information to the determination device 2. The determination device 2 determines a terrain profile type GP Type from the terrain profile GP. It is assumed here that twenty different terrain profile types GP 1 to GP 20 are provided and the determination device 2 assigns the determined terrain profile GP to one of these terrain profile types GP 1 to GP 20.

[0036] In addition to the target route S and the terrain profile GP for completing the task, comfort aspects must also be considered. It is therefore assumed that the detection system 2 is wirelessly connected to a weather forecast system 8 and determines temperature data for the locations "Charging Station 4", "A", "B", "C", and "Charging Station 4" over time and calculates an average temperature T v from this.

[0037] As can be seen from the above, in the example shown here, the determination device 2 has determined the parameters "distance S target", "terrain profile type GP type", and "predicted average temperature T v". This selection has been made for reasons of clarity; in fact, any number of parameters can of course be determined with the necessary accuracy and used for the further determination of the required usable capacity of the battery 5, as described below as an example.

[0038] In the further course of the method, the determination device 2 transfers the determined parameters "distance S target", "terrain profile type GP type" and "predicted average temperature T v " to a calculation device 9, which determines the required usable capacity of the battery 5 from the parameters. In the example considered here, it is assumed that the predicted average temperature T v is 20°C. To determine the required capacity, the calculation device 9 is operatively connected to a first storage device 10. In order to arrive at a required capacity from the parameters, the calculation device 9 uses the content of the first storage device 10. This contains a plurality of characteristic maps, each in digital form. Each of these characteristic maps is valid for a specific temperature T s and indicates the required usable capacity K as a function of the distance S and terrain profile type GP type.If the predicted average temperature T v lies between two specific temperatures T s for which maps are available, interpolation is performed between the maps, as is usual in such cases. For the terrain profile type, it is assumed that a subdivision into twenty different terrain profile types GP 1 to GP 20 is planned. For better understanding, one of these maps is shown in . Fig. 2 shown in a very simplified way as an example.

[0039] The Fig. 2shows a three-dimensional Cartesian coordinate system in which the dependence of the required capacity K on the distance traveled S and the terrain profile type GP Type is shown in the form of a characteristic map. The characteristic map applies to a temperature T v of 20°C, i.e. the average temperature T v determined by the determination device 2. For other temperatures T v, other characteristic maps apply which are not shown here. The characteristic map is used within two limits of a minimum capacity K min (20 °C) and a maximum capacity K max (20 °C). The minimum capacity K min (20 °C) is set in such a way that any influence on the aging of the battery at capacities smaller than K min (20 °C) is insignificant and can be disregarded.This procedure means that after each charge, depending on the type of terrain profile to be driven over, a minimum driving distance between S min (GP 1 ) and S min (GP 20 ) is available, even if other parameters for calculating the required capacity have not been determined. The other limitation of the usable range of the characteristic map is defined by a maximum permissible capacity K max (20°C) of the battery at 20°C. This is the maximum net capacity permissible for the battery at a temperature of 20°C. With this maximum permissible capacity K max (20°C), different maximum driving distances S max can be covered, depending on the type of terrain profile being driven over, namely between S max (GP 20 ) and S max (GP 1 ).

[0040] For the example described here, it is assumed that the investigative facility 2 ( Fig. 1) has transmitted the driving distance S soll , the terrain profile type GP 10 and the predicted average temperature T v = 20°C to the calculation device 9. This takes from the characteristic map according to Fig. 2 a required capacity K soll(20°C) and transmits this to a determination device 11. The task of the determination device 11 is to determine an SoC window from the required capacity K soll(20°C). As already explained above, the SoC window is a range within which a battery is charged.

[0041] For a better understanding, different SoC windows and their relationship with the capacity of a high-voltage battery system are shown in Fig. 3shown diagrammatically. There, a battery 5.1 is shown, represented in the form of a capacity diagram. According to the illustration, the battery has a gross capacity K gross. However, this cannot be fully utilized because use in the upper and lower limit ranges would lead to extreme aging phenomena in the form of irreversible capacity loss. For this reason, the manufacturer usually specifies a net capacity K net within which the battery must be operated in order to achieve a guaranteed number of cycles, i.e. a guaranteed number of charge-discharge cycles. This means that the battery must not be charged up to its gross capacity K gross and must not be discharged below a specified capacity. The usable range therefore lies within a window, which is usually referred to as the SoC window.In the example considered here, this usable range is assumed to be the maximum usable SoC window SoC-F max in order to optimize battery aging. This maximum usable SoC window SoC-F max is assigned a first value as the upper limit OG(SoC-F max ), up to which the battery may be charged, and a second value as the lower limit UG(SoC-F max ), up to which the battery may be discharged. Since both lowering the upper limit to a value less than OG(SoC-F max ) and raising the lower limit to a value greater than UG(SoC-F max ) have a positive effect on battery aging, the limits of the SoC window are defined according to the invention by the actually required capacity if this is less than the net capacity. If the required capacity is greater than the net capacity, the maximum permissible SoC window SoC-F max is used.In the event that the determined required capacity is below a minimum capacity whose variable use no longer provides any aging benefits, the example chosen here proposes charging the battery to a minimum capacity K min . The resulting SoC window has the value OG(SoC-F min ) as the upper limit and the value UG(SoC-F min ) as the lower limit. In the example considered, the range between the net capacity K net and the minimum capacity K min represents the variably usable capacity range.The variable capacity range here means that if the required capacity K target to cope with a predictively determined task - in this case a driving distance S target - is greater than the minimum capacity K min and less than the net capacity K net, an SoC window SoC-F target is derived from the required capacity K target, to which a first value is assigned as the upper limit OG(SoC-F target) and a second value as the lower limit UG(SoC-F target). The upper limit OG(SoC-F target) is smaller than OG(SoC-F max) and the lower limit UG(SoC-F target) is greater than UG(SoC-F max), so that charging the battery up to the upper limit OG(SoC-F target) and discharging the battery down to the lower limit UG(SoC-F target) has a positive effect on battery aging.For the use of a battery operated in this way, this means that the net capacity K net specified by the manufacturer is available to the user for a greater number of cycles than that specified by the manufacturer.

[0042] How to Fig. 1As described above, the task of the determination device 11 is to determine an SoC window from the required capacity K soll(20°C). For this purpose, the determination device 11 uses a second memory device 12. To determine the SoC window, an access to the contents of the memory device 12 is derived from the required capacity K soll(20°C), which access contains the data of a large number of SoC windows in the form of values ​​for their upper and lower limits. In the example considered here, the determination device 11 uses the required capacity K soll(20°C) - as addressing, so to speak - to extract from the memory device 12 a first value as the upper limit OG(SoC-F soll ) and a second value as the lower limit UG(SoC-F soll ) of the SoC window SoC-F soll and transmits these to a setting device 13 of a battery management system 14, which controls the charging / discharging process of the battery 5.The battery management system 14 controls the charging process of the battery 5 such that it is charged up to the upper limit OG(SoC-F soll ) of the SoC window SoC-F soll . During the next operating cycle of the vehicle to cover the distance S soll , the battery management system 14 controls the discharging process such that the battery 5 is not discharged below the lower limit UG(SoC-F soll ) of the SoC window SoC-F soll . Alternatively, it can be provided that automatically or upon input from the driver, a part of the capacity range below the lower limit UG(SoC-F soll ) of the required capacity K soll and above the lower limit UG(SoC-F max ) of the net capacity K net is released as a capacity reserve when requested by the driver.

[0043] Numerous variations are conceivable in the embodiment of the example described above. For example, it is possible to record the driver's personal preferences and characteristics in advance, for example, using a driver analysis system (not shown), and to incorporate them as a key figure in determining the expected capacity requirement. Furthermore, it is possible to design the arrangement and method in such a way that data is collected during operation and, in the manner of a self-learning system, correction factors are determined that are incorporated into the calculation of the expected capacity required to perform a subsequent task. Another application shows Fig. 4in the form of a flow chart. In this example, it is assumed that the task to be completed is essentially always the same and is subject to only minor fluctuations. This is the case, for example, when a software tool powered by a battery always carries out the same work processes during two charging processes, for example, during a work shift on an assembly line. It is also assumed that the net capacity of the battery is designed such that the software tool can safely complete the task to be completed with one charge and that a safety reserve normally remains in the battery. For the control-technical implementation, it is further assumed that the charge / discharge control is part of the tool and that the tool has a switching device with which a maximum charge can be requested. In the following description, reference is also made to the representation in Fig. 3Reference is made to the above Fig. 3 The statements made therefore also apply, for example, to Fig. 4 , with the exception of the statements on the minimum capacity K min , which in the example according to Fig. 4 is not provided for.

[0044] Based on the above, the procedure can be carried out as described in Fig. 4 The following exemplary procedural steps are included. Steps that must be performed manually are indicated by dashed lines.

[0045] Process steps: VS1: A charging process is initiated by manually inserting the tool into a charging station. VS2: Query by the charge / discharge control: Has the "maximum charge" switching device been set? If "yes," continue with process step VS3; if "no," continue with process step VS5. VS3: The charge / discharge controller sets the SoC window SoC-F max with a first value as the upper limit OG(SoC-F max ) and a second value as the lower limit UG(SoC-F max ), charges the battery to the net capacity K net, and stores the net capacity K net as the target capacity K target . Continue with process step VS4. VS4: The tool is inserted. While the task is being performed, the following process runs automatically, controlled by the loading / unloading control: VS4.11 The charge / discharge control cyclically determines the remaining capacity K Rest of the battery through a measuring process. VS4.12 The charge / discharge control cyclically determines whether K gross minus K net is less than the measured residual capacity K rest . If "yes," continue with VS4.2; if "no," continue with VS4.11. VS4.2 The charge / discharge control prompts immediate charging by means of an acoustic and / or optical and / or haptic signal and sets the "maximum charge" switching device. After completing the task or after a signal is given, charging is initiated manually. Continue with process step VS1. VS5: The charge / discharge controller determines the remaining capacity K of the battery through a measurement process. Continue with process step VS6. VS6: The charge / discharge control checks whether the remaining capacity KRemain of the battery is greater than a specified reserve capacity KReserve. If "yes," continue with process step S7; if "no," continue with process step S9. VS7 The charge / discharge controller calculates a new target capacity K target (new) by retrieving the stored target capacity K target, subtracting the measured remaining capacity K rest from it, and adding the specified reserve capacity K reserve. The charge / discharge controller then saves the new target capacity K target (new) as the currently valid target capacity K target and determines an SoC window SoC-F target from the stored target capacity K target. Continue with process step VS8. VS8 To control the charging / discharging process, the charge / discharge controller sets the SoC window SoC-F target with the first value as the upper limit OG(SoC-F target) and the second value as UG(SoC-F target), and charges the battery to the stored target capacity K target. Continue with process step VS11. VS9 The charge / discharge control calculates a new target capacity K target (new) by retrieving the stored target capacity K target and adding the specified reserve capacity K reserve. Continue with process step VS10. VS10 Query by the charge / discharge control: If the new target capacity K target (new) is less than K net, if "yes" continue with process step VS11, if "no" continue with process step VS12. VS11 The charge / discharge controller saves the new target capacity K target (new) as target capacity K target . Continue with process step VS13. VS12 The charge / discharge control saves the net capacity K net as the target capacity K target . Continue with process step VS13. VS13 To control the charging / discharging process, the charge / discharge controller sets the SoC window SoC-F target corresponding to the stored target capacity K target with the first value as the upper limit OG(SoC-F target) and the second value as the lower limit UG(SoC-F target), and charges the battery to the target capacity K target. Continue with process step VS4.

[0046] The method described above ensures that an SoC window is used for the battery charging and discharging process that is always within the maximum permissible SoC window SoC-F max , and in the majority of cases well within this window, so that battery aging is positively influenced and the achievable number of cycles is increased. In an embodiment of the method described above, it can be provided that the "maximum charge" switching device can also be set manually by the operator actuating an input device. This is necessary, for example, if the tool operating according to the method described above is used for a new purpose or in a different location. A tool equipped with the features described above automatically searches for a target capacity K target based on the previous work cycle, in accordance with a self-learning process.The SoC window SoC-F target associated with the target capacity K target is in the majority of cases smaller than the SoC window SoC-F net assigned to the net capacity K net and lies within the limits of the SoC window SoC-F net assigned to the net capacity K net, so that optimized aging of the battery is achieved.

[0047] Although designed for a software tool, the method described above can, in principle, also be used for a vehicle application if the distance to be covered between two charging processes is essentially the same. For example, it is conceivable to use vehicles in a postal or parcel delivery service in such a way that essentially the same distance is always covered. In this case, the method according to Fig. 4 be transferred to this application.

[0048] The invention allows a predictive determination of the SoC operating window of battery 5 for upcoming journeys. An evaluation unit can determine the SoC operating window based on the following parameters: 1. Information about planned routes (smart calendar query) to determine the required range; 2. Additional requests from the driver (e.g., auxiliary heating, trip to the hardware store with a trailer, camping, etc.); 3. Weather forecast to determine air conditioning requirements as secondary consumption; 4. Electrical consumption from previous trips (evaluation of recent trips); usage-specific consumption values; Based on the above parameters, the evaluation unit can control the HV charging management and the battery management system.

[0049] A core concept of the invention is that each charging process of the battery 5 is controlled depending on the outside temperature and the resulting air conditioning requirements in such a way that the driver is always provided with a reliable, fixed / constant range, in particular over the guaranteed duration of the battery's characteristics. For example, the customer can be provided with a fixed / constant range of 200 km, as can be seen from the two diagrams of the Figure 5 The upper diagram illustrates the electrical energy requirement per 100 km in kWh over the months of a year. The lower diagram illustrates the corresponding, required HV battery energy content for each month, which enables a constant range of 200 km in kWh. As can be seen from the Figure 5As can be seen, heating demand is high in winter, while cooling demand is high in summer (compared to spring / autumn), which increases electrical consumption. Therefore, a higher energy content must be loaded into the battery to meet the power requirements of the HV auxiliary loads while maintaining the guaranteed 200 km range available to the driver.

[0050] The above facts are explained by the Figures 6 to 9 explained again: In a first variant ( Figure 6) the vehicle must have a battery 5 with a gross energy content of 80 kWh. For example, the outside temperature is 18°C. A typical delivery service driving cycle is planned as an example. The electrical consumption for this specific cycle is estimated based on the current outside temperature. The required battery capacity (e.g., 50 kWh) to provide a constant range (i.e., 200 km) is calculated and transmitted, for example, to an intelligent charger. Battery 5 is charged via the charger up to an energy content of 50 kWh, for example.

[0051] In contrast to the first variant above ( Figure 6 ) is in the second version ( Figure 7) the outside temperature is 35°C. A classic delivery driving cycle is also planned. Due to the higher outside temperature, the air conditioning requirement will increase. The estimated electrical consumption for this cycle will also increase accordingly. In order to provide a constant range (for example, 200 km) with increased electrical consumption, the required energy content of the battery (compared to Figure 6 ) is increased (for example, by 5%). With the help of intelligent charging management, the battery is now charged to the required energy content (50 kWh + 5% = 52.5 kWh).

[0052] Alternatively, a third variant ( Figure 8) the outside temperature is 0°C. A journey to work is planned, for example. In this case, the electrical consumption per 100 km (i.e. drive + HV auxiliary consumers) from previously evaluated journeys to work with similar outside temperatures is taken into account. In addition, the driver selects the pre-conditioning of the vehicle interior to 22°C the evening before, for example via his mobile phone, which results in a reduced power requirement for the HV heaters in the interior. The driver can also indicate that he can recharge his vehicle at work. Based on the above information, the evaluation unit can determine the required HV battery charge (plus an inaccuracy allowance). For example, for a battery with a gross energy content of 80 kWh and an energy consumption of approximately 20 kWh per 100 km, the energy content charged via the charger can be 60%.

[0053] According to a fourth variant ( Figure 9 ) the outside temperature may be 15°C. A trip to the hardware store with a trailer is planned. The required range to hardware stores in the nearby area can be determined using the navigation device or by accessing private calendars / entering data in vehicle apps. The electrical energy requirement per 100 km (drive + HV auxiliary consumers) from previously evaluated trips with a trailer and with similar outside temperatures is taken into account. The maximum payload of the trailer is also taken into account. Based on the above information, the evaluation unit can determine the required battery charge (plus an inaccuracy allowance).

[0054] For example, a battery with a gross energy capacity of 80 kWh would require approximately 35 kWh of energy per 100 km. Due to the higher (predicted) consumption, a higher amount of energy is charged into the battery, for example, 70 kWh. List of reference symbols

[0055] 1Charge / discharge control 2Determination device 3Charging plug 4Charging station 5, 5.1High-voltage battery system 6Electronic appointment calendar 7Route calculation system 8Weather forecast system 9Calculation device 10First storage device 11Determination device 12Second storage device 13Setting device 14Battery management system VS1 to VS14Procedure steps GP type(20°C) Terrain profile type at 20°C GP1 to GP20Terrain profile types K gross Gross capacity (of battery 5) K net Net capacity (of battery 5) K target Target capacity (of battery 5) K min Minimum capacity (of battery 5) K 20°C Capacity (of battery 5) at 20°C K target(20°C) Target capacity (of battery 5) at 20°C min(20^C) Minimum capacity (of battery 5) at 20°CK max(20^C) Maximum capacity (of battery 5) at 20°CS (20°C) Driving distance at 20°CS min (GP1) minimum driving distance for terrain profile type 1 S min (GP20) minimum driving distance for terrain profile type 20 S max (GP1) maximum driving distance atTerrain profile type 1 S max (GP20) maximum driving distance for terrain profile type 20 S target target driving distance SoC-F max maximum SoC window SoC-F target target SoC window SoC-F min minimum SoC window UG(SoC-F max ) lower limit of maximum SoC window OG(SoC-F max ) upper limit of maximum SoC window UG(SoC-F target ) lower limit of target SoC window OG(SoC-F target ) upper limit of target SoC window UG(SoC-F min ) lower limit of minimum SoC window OG(SoC-F min ) upper limit of minimum SoC window

Claims

1. Method for charge / discharge control of a high-voltage battery system (5), wherein different usable capacities of the battery of the high-voltage battery system (5) can be adjusted by selecting different SoC windows, wherein - in a process that is upstream of a charging process, at least one parameter is determined, which parameter predicts a usable capacity (Ksoll) of the battery required until the next charging process, - the at least one parameter is converted into a required usable capacity (Ksoll), - using the required usable capacity (Ksoll), a target SoC window (SoC-Fsoll) that optimizes the aging state of the battery is defined such that the target SoC window (SoC-Fsoll) is smaller than a maximum permissible SoC window (SoC-Fmax) and is located within the maximum permissible SoC window (SoC-Fmax), - the target SoC window (SoC-Fsoll) is adjusted, - the battery (5) is charged within the range specified by the target SoC window (SoC-Fsoll), - the discharging of the battery (5) occurs in the range specified by the target SoC window (SoC-Fsoll), wherein the required usable capacity is obtained from a predicted task, and wherein the predicted task is to complete a previously determined travel route of a fully or partially electrically operated vehicle comprising the high-voltage battery system (5), and wherein the travel route is determined by means of a route calculation system (7), wherein the required usable capacity is additionally obtained from environmental conditions, and wherein the environmental condition is the ambient temperature, and wherein the ambient temperature is an ambient temperature which is predefined by season and / or time of day and location, and is stored in a memory unit, and wherein the ambient temperature to be considered in each case is extracted from the memory unit using at least one date and / or time and location, and wherein a plurality of predicted ambient temperatures are determined from a weather forecast system (8) in a location-based and time-based manner, wherein the ambient temperatures obtained in this way are linked to the travel route in a location-based and time-based manner, and wherein the parameter is determined from these linked data, and wherein the required usable capacity is additionally obtained from at least one of the following parameters, specifically a personal energy overconsumption or personal energy underconsumption of an operator, wherein the personal energy overconsumption or energy underconsumption is obtained as a parameter from upstream personal consumption analysis.

2. Method according to claim 1, characterized in that the predicted usable capacity required until the next charging process includes a safety reserve.

3. Method according to either of the preceding claims, characterized in that the battery (5) is a high-voltage traction battery of the fully or partially electrically operated vehicle, and in that the predefined task is to cover a minimum travel distance at a predefined height profile.

4. Method according to claim 3, characterized in that each charging process is controlled depending on, among other things, the ambient temperature and the resulting air conditioning demand, such that the driver is always provided with a reliable, fixed / constant range.

5. Method according to claim 3 or 4, characterized in that the planning system contains the order of the locations to be traveled to and / or the time of day at which an arrival at at least one location is planned, and in that the route calculation system (7) determines a travel route therefrom.

6. Method according to any of the preceding claims, characterized in that the at least one parameter is obtained from the evaluation of at least one previous charge-discharge cycle.

7. Arrangement for charge / discharge control for carrying out the method according to any of the preceding claims, wherein the arrangement for charge / discharge control - contains a determining device (2) which determines at least one parameter, wherein the at least one parameter represents the capacity (Ksoll) of the battery (5) required until the next charging process, - contains a calculating device (9) which calculates the required capacity (Ksoll) from the parameter, - contains a defining device (11) which defines an SoC window (SoC-Fsoll) that optimizes the aging state of the battery, such that the target SoC window (SoC-Fsoll) is smaller than a maximum permissible SoC window (SoC-Fmax) and is located within the maximum permissible SoC window (SoC-Fmax), - contains an adjusting device which adjusts the SoC window (SoC-Fsoll), - the battery (5) is charged within the range specified by the target SoC window (SoC-Fsoll), - the discharging of the battery (5) occurs in the range specified by the target SoC window (SoC-Fsoll), wherein the required usable capacity is obtained from a predicted task, and wherein the predicted task is the completion of a previously determined travel route of a fully or partially electrically operated vehicle comprising the high-voltage battery system, wherein the travel route can be determined by means of a route calculation system (7), wherein the required usable capacity can additionally be obtained from environmental conditions, and wherein the environmental condition is the ambient temperature, and wherein the ambient temperature is an ambient temperature which is predefined by season and / or time of day and location, and is stored in a memory unit, and wherein the ambient temperature to be considered in each case can be extracted from the memory unit using at least one date and / or time and location, and wherein a plurality of predicted ambient temperatures can be determined from a weather forecast system (8) in a location-based and time-based manner, wherein the ambient temperatures obtained in this way can be linked to the travel route in a location-based and time-based manner, and wherein the parameter can be determined from these linked data, and wherein the required usable capacity is additionally obtained from at least one of the following parameters, specifically a personal energy overconsumption or personal energy underconsumption of an operator, wherein the personal energy overconsumption or energy underconsumption is obtained as a parameter from upstream personal consumption analysis.