ADAPTER DEVICE AND METHOD FOR CHARGING A VEHICLE

• US 20110270476A1
• Filed: 05/06/2009
• Published: 11/03/2011
• Est. Priority Date: 07/08/2008
• Status: Abandoned Application

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Ferscha, Alois, Jansch Dos Santos Rocha, Marcos, Franz, Marquart, Zachhuber, Doris, Hechinger, Manfred, Doppler, Jakob, Zeidler, Andreas
• Application Number:
  US13/003,463
• Publication Number:
  US 20110270476A1
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2250/18 by enquiring driving style
• CPC Class Codes: B60L 2260/46 by self learning
• CPC Class Codes: B60L 2260/54 Energy consumption estimation
• CPC Class Codes: B60L 53/14 Conductive energy transfer
• CPC Class Codes: B60L 53/32 by charging in short intervals along the itinerary, e.g. during short stops
• CPC Class Codes: B60L 53/64 Optimising energy costs, e.g. responding to electricity rates
• CPC Class Codes: B60L 53/65 involving identification of vehicles or their battery types
• CPC Class Codes: B60L 53/665 Methods related to measuring, billing or payment
• CPC Class Codes: H02J 7/00 Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
• CPC Class Codes: Y02T 10/64 Electric machine technologies in electromobility
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 Electric charging stations
• CPC Class Codes: Y02T 90/14 Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 30/14 Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing

Abstract

An adapter apparatus has an interface for detecting internal vehicle operation data containing factors which report driving habits according to lifestyle, and an interface for detecting details related to the fluctuation of energy prices. The adapter apparatus further has a device for detecting and planning requirements, the device being configured for deducing an energy requirement profile using the vehicle operation data and for producing a future requirement plan based on at least one of the named factors. The device further being suitable for deducing the duration and frequency of vehicle down times by incorporating the requirement plan and having a charging optimizing device which is configured for comparing the vehicle down times with the energy price fluctuation. Details for producing a vehicle charging plan which is optimized for time and/or price and is based on the results of the comparison. The apparatus further having a charging control unit which is configured for charging the vehicle from an energy store in a manner controlled by the charging plan.

Claims

1-17. -17. (canceled)

18. An adapter device for charging a vehicle, the adapter device comprising:

an interface for acquiring internal vehicle operating data including factors indicating lifestyle-dependent driving habits;

an interface for acquiring information about energy price movements;

a requirement identification and planning unit configured to deduce an energy requirement profile from the vehicle operating data and to generate a future requirement plan on a basis of at least one of the factors, and further configured to deduce a duration and frequency of idle times of the vehicle using the future requirement plan;

a charging optimization unit for comparing the idle times of the vehicle with the information about energy price movements and to generate at least one of a time-optimized or price-optimized charging plan for the vehicle on a basis of a comparison result; and

a charging control unit for charging an energy store of the vehicle in a manner controlled by the charging plan.

19. The device according to claim 18, further comprising an interface for acquiring context information describing in more detail a current situation of the vehicle and having an effect on consumption, including at least one of profile data of a vehicle owner, traffic information or weather information, and said requirement identification and planning unit is additionally configured to deduce the energy requirement profile from the context information.

20. The device according to claim 19, wherein at least one of said interfaces is configured for wireless acquisition of at least one of the vehicle operating data, the energy price information or the context information.

21. The device according to claim 18, further comprising a memory unit for storing the information concerning energy price movements.

22. The device according to claim 18, wherein the device is an external adapter between an energy source and the energy store of the vehicle.

23. The device according to claim 18, wherein the device is an adapter implemented as an integral part of the vehicle.

24. A method for recognizing vehicle usage patterns, including recognizing driving habits or a driving style for calculating insurance models, which comprises the steps of:

providing an adapter device for charging a vehicle, the adapter device having an interface for acquiring internal vehicle operating data including factors indicating lifestyle-dependent driving habits, an interface for acquiring information about energy price movements, a requirement identification and planning unit configured to deduce an energy requirement profile from the vehicle operating data and to generate a future requirement plan on a basis of at least one of the factors and further configured to deduce a duration and frequency of idle times of the vehicle using the future requirement plan, a charging optimization unit for comparing the idle times of the vehicle with the information about energy price movements and to generate a time-optimized and/or price-optimized charging plan for the vehicle on a basis of a comparison result, and a charging control unit for charging an energy store of the vehicle in a manner controlled by the charging plan; and

generating the vehicle usage patterns via the adaptive device.

25. A method for charging a vehicle, which comprises the steps of:

acquiring and storing internal vehicle operating data containing factors indicating lifestyle-dependent driving habits;

deducing an energy requirement profile from the vehicle operating data and generating a future requirement plan created in dependence on at least one of the factors;

deducing a duration and frequency of idle times of the vehicle using the future requirement plan;

acquiring energy price movements and comparing the idle times of the vehicle with the energy price movements; and

producing a time-optimized and/or price-optimized charging plan for the vehicle on the basis of a comparison result.

26. The method according to claim 25, which further comprises generating the future requirement plan for the vehicle by determining daily travel times and average journey duration from a characteristic curve of an actual energy consumption of journeys made.

27. The method according to claim 26, which further comprises using at least one of operating times or route data to generate the future requirement plan for the vehicle.

28. The method according to claim 25, which further comprises generating the future requirement plan for the vehicle by acquiring positions of the vehicle and deducing therefrom spatial trip-chaining patterns indicating daily recurring destinations and their sequential order.

29. The method according to claim 25, wherein, in order to generate the future requirement plan, context information external to the vehicle is additionally used which describes in greater detail a current situation of the vehicle and has an effect on consumption.

30. The method according to claim 25, wherein, in an event of low charge caused by unforeseeable journeys, a user of the vehicle is given information about unscheduled charging options.

31. The method according to claim 25, which further comprises acquiring the energy price movements by interrogating an Internet-based energy trading platform.

32. The method according to claim 25, which further comprises acquiring the energy price movements by periodically installing a software update.

33. The method according to claim 25, which further comprises activating the charging plan dependently controlled power feed to the vehicle as soon as the latter is connected to an energy source.

34. The method according to claim 25, which further comprises implementing a pattern recognition process, a machine learning process or an artificial intelligence process to generate requirement plans.

35. The method according to claim 25, wherein, in order to generate the future requirement plan, context information external to the vehicle and selected from the group consisting of profile data of a vehicle owner, traffic information, and weather information, is additionally used which describes in greater detail a current situation of the vehicle and has an effect on consumption.