Execution of charge session swap based on charging priority
US-2019263271-A1 · Aug 29, 2019 · US
US10875419B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10875419-B2 |
| Application number | US-201916296406-A |
| Country | US |
| Kind code | B2 |
| Filing date | Mar 8, 2019 |
| Priority date | Sep 9, 2016 |
| Publication date | Dec 29, 2020 |
| Grant date | Dec 29, 2020 |
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A charging system controls an optimum charging process of an at least partially electrically operated vehicle. The electrically operated vehicle has an energy accumulator. The charging system has at least one power source with which the energy accumulator is connected and can be charged, and at least one back end server which can automatically determine an optimum charging plan for charging the energy accumulator based at least on technical state data of the vehicle and an electricity rate that is assigned to the energy source. In this way, when the energy accumulator is connected to the power source, the technical state data of the vehicle is automatically transmitted to the back end server. After the back end server receives the technical status data of the vehicle, the back end server determines the optimum charging plan. The back end server can control the charging process of the energy accumulator according to the optimum charging plan.
Opening claim text (preview).
What is claimed is: 1. A charging system for controlling an optimum charging process of an at least partly electrically operated vehicle, wherein the at least partly electrically operated vehicle has an energy store, comprising: at least one electricity source to which the energy store is able to be connected and by way of which it is able to be charged; at least one back-end server that is able automatically to identify an optimal charging plan for charging the energy store on the basis at least of technical state data from the vehicle and an electricity tariff that is assigned to the electricity source; and a digital electricity meter that is able to detect a current electricity consumption of a household associated with the electricity source, wherein the back-end server is additionally able to calculate the optimum charging plan based on the current electricity consumption and a maximum electricity capacity of the associated household, when the energy store is connected to the electricity source, the technical state data are transmitted automatically from the vehicle to the back-end server, the back-end server identifies the optimum charging plan after receiving the technical state data from the vehicle, and the back-end server is able to control the charging process of the energy store in accordance with the optimum charging plan. 2. The charging system as claimed in claim 1 , further comprising: an input device configured to receive an input from a user of the vehicle to define a desired departure time or a desired state of charge of the energy store at the end of the charging process. 3. The charging system as claimed in claim 1 , wherein the technical state data comprise a current state of charge of the energy store and position data of the vehicle. 4. The charging system as claimed in claim 1 , wherein the back-end server is able to detect changes in the electricity consumption relevant to the calculation of the optimum charging plan and perform a new calculation of the optimum charging plan taking into account these changes in the electricity consumption, and the back-end server is able to control the charging process of the energy store in accordance with the new calculation of the optimum charging plan. 5. The charging system as claimed in claim 4 , wherein the back-end server is additionally able to control smart household devices associated with the electricity source when creating the optimum charging plan, such that an optimum electricity consumption is present in the household associated with the electricity source during charging times calculated for the charging process. 6. The charging system as claimed in claim 1 , further comprising: a photovoltaic installation that is able to feed electricity to a household associated with the electricity source; wherein the back-end server is additionally able to calculate the optimum charging plan taking into account a current electricity infeed through the photovoltaic installation. 7. The charging system as claimed in claim 6 , wherein the back-end server is able to detect changes in the electricity infeed through the photovoltaic installation and perform a new calculation of the optimum charging plan taking into account these changes in the current electricity infeed, and the back-end server is able to control the charging process of the energy store in accordance with the new calculation of the optimum charging plan. 8. The charging system as claimed in claim 1 , wherein the electricity source is a wall charging station, and the wall charging station is able to receive the optimum charging plan from the back-end server and control implementation of the optimum charging plan. 9. A method for controlling an optimum charging process of an at least partly electrically operated vehicle, wherein the at least partly electrically operated vehicle has an energy store, the method comprising the steps of: providing at least one electricity source to which the energy store is able to be connected and by way of which it is able to be charged; providing at least one back-end server that is able automatically to identify an optimum charging plan for charging the energy store on the basis at least of technical state data from the vehicle and an electricity tariff that is assigned to the electricity source; receiving, by the back-end server, the technical state data automatically transmitted from the vehicle when the energy store is connected to the electricity source; detecting a current electricity consumption of a household associated with the electricity source; automatically identifying the optimum charging plan using the back-end server after receiving the technical state data from the vehicle; calculating the optimum charging plan based on the current electricity consumption and a maximum electricity capacity of the associated household; and controlling the charging process of the energy store in accordance with the optimum charging plan using the back-end server.
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