Configurable energy management system for a vehicle

Abstract

Configurable energy management system (10) for charging an electric vehicle, comprising: an energy storage device (16) for storing energy; an in-vehicle source (12) of renewable energy for generating electrical energy to charge the in-vehicle energy storage device (16); at least one source of renewable energy outside the vehicle to provide electrical energy to the vehicle for charging the vehicle's internal energy storage device (16); a vehicle communication module (52) for sending and receiving data; an integration module for integrating parameter data of in-vehicle energy, parameter data of in-vehicle renewable energy, parameter data of renewable energy outside the vehicle, user parameter data, web-based data and cloud computing data (56), wherein the cloud computing data (56) is obtained from at least one information source and includes data relating to grid electricity, vehicle fuel information, electric charging stations and weather information; and a user interface device (50) for communicating with the vehicle communication module (52) and the integration module, wherein the user interface device (50) is a smartphone and transmits the user parameter data to the integration module, wherein the user parameter data includes a prioritization of preferred parameters for charging the vehicle's internal energy storage device (16), wherein the preferred parameters include a time-based index and / or a cost-based index and / or a green index; wherein the integration module identifies an optimal energy source for charging the vehicle based on the parameter data of in-vehicle energy, the parameter data of in-vehicle renewable energy, the parameter data of renewable energy outside the vehicle, the user parameter data, the web-based data and the cloud computing data (56), wherein the cloud computing data (56) is received by the smartphone and sent to the integration module.

Description

BACKGROUND OF THE INVENTION

[0001] One embodiment relates generally to energy management in vehicles.

[0002] Electric vehicles and hybrid electric vehicles use stored electrical energy to power a vehicle operating system, such as an engine, as well as multiple electrical devices within the vehicle. Various energy sources can be used to return power to the vehicle energy storage device during recharging periods. Such energy sources can include solar energy, home energy (e.g., wind turbines and other home energy-generating devices), and electricity from a power grid. Apart from a default strategy at the vehicle's control unit, it is the user's choice as to which energy source to select. The user's choice may not always be the most ideal from an economic perspective (e.g., expensive drawing from a grid during peak hours) or may be impractical (e.g., solar power when there is insufficient light).

[0003] It would be beneficial to have a management system that could indicate which alternative is the best charging strategy given the time constraints and the environmental and vehicle conditions.

[0004] US 2009 / 0 313 098 A1 discloses a system of a grid-based energy preference service for managing charging preferences for an electric vehicle, wherein the vehicle has an on-board energy generation mechanism. The vehicle can be charged at a charging station. The vehicle and charging station are connected to a grid for sending and receiving data. Servers and clients, where data processing can be performed, are also connected to the grid. An energy preference service is used to charge the vehicle and stores preferences regarding charging. The preferences can be entered via a communication device. An energy decision assistant monitors real-time data such as weather, route, and traffic information. A bid service receives bids from providers. An energy transaction planner generates a transaction plan based on the preferences. Further prior art is known from WO 2010 / 042 550 A2. SUMMARY OF THE INVENTION

[0005] The object of the invention is to provide an improved configurable energy management system.

[0006] To achieve this objective, a configurable energy management system having the features of claim 1 is provided. Advantageous embodiments of the invention can be found in the dependent claims, the description, and the drawings.

[0007] One advantage of an embodiment is a configurable energy management charging system for an electric vehicle, in which the charging method is determined based on preferred parameters, vehicle operating conditions, and environmental conditions. The preferred parameters are prioritized by a user and include a time-based index, a cost-based index, and a green index. The vehicle operating condition data, environmental condition data, and the preferred parameter data are obtained and analyzed to recommend an optimal charging strategy that supports the user's requirements while considering factors that have a direct and indirect influence on the charging process.

[0008] One embodiment contemplates a configurable energy management system for charging an electric vehicle. An energy storage device stores energy. An on-vehicle renewable energy source generates electrical energy to charge the on-vehicle energy storage device. The at least one off-vehicle renewable energy source supplies electrical energy to the vehicle to charge the on-vehicle energy storage device. A vehicle communication module transmits and receives data.An integration module integrates on-vehicle energy parameter data, on-vehicle renewable energy parameter data, off-vehicle renewable energy parameter data, user parameter data, web-based data, and cloud computing data, wherein the cloud computing data is obtained from at least one information retrieval source and includes data related to grid electricity, vehicle fuel information, electric charging stations, and weather information. A user interface device is a smartphone and communicates with the vehicle communication module and the integration module. The user interface device transmits the user parameter data to the integration module. The user parameter data includes a prioritization of preferred parameters when charging the on-vehicle energy storage device.The preferred parameters include a time-based index, a cost-based index, and / or a green index. The web-based data is downloaded for use by the integration module. The integration module identifies an optimal energy source for charging the vehicle based on the on-vehicle energy parameter data, the on-vehicle renewable energy parameter data, the off-vehicle renewable energy parameter data, the user parameter data, the web-based data, and the cloud computing data, with the cloud computing data being obtained by the smartphone and sent to the integration module. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a block diagram of a personalized energy management system of an electric vehicle. Fig. 2 is a flowchart of a method for determining the charging strategy. DETAILED DESCRIPTION

[0009] In Fig. 1, a personalized charging energy management system 10 for selectively controlling the electrical energy delivered to various components of a vehicle is shown. The system 10 includes a vehicle power distribution system 11 that includes a renewable energy source 12, such as an on-board solar panel array, coupled to a solar control module 14 to distribute electrical energy to either an energy storage device 16 or a preconditioning device, such as an electric motor 18 (e.g., HVAC fan motor). It should be understood that the preconditioning device is not limited to a fan motor, but may include any propulsion system component.

[0010] The solar panel assembly 12 includes an array of panels constructed from solar cells. The panels are connected together, typically in series, so that the voltage is additive and a desired voltage output can be achieved. The energy captured by the solar panel assembly 12 excites electrons in the solar cells to generate electricity. However, the solar cells can be coupled in a series-parallel configuration to achieve a desired module voltage. The electricity generated by the solar panel assembly 12 is in the form of direct current (DC).

[0011] The solar control module 14 includes a processor 20, a DC-DC converter 22, and a switch 24. The DC-DC converter 22 is coupled between the solar panel assembly 12 and the switch 24. The DC-DC converter 22 either converts a low DC voltage generated by the solar panel assembly 12 to a high DC voltage or converts a high DC voltage generated by the solar panel assembly 12 to a low DC voltage. A current measuring device 26 may be coupled between the solar panel assembly 12 and the DC-DC converter 22 to monitor the current flow from the solar panel assembly 12.

[0012] The switch 24 selectively couples the solar panel assembly 12 via the DC-DC converter 22 to either the energy storage device 16 or the motor 18. Coupling the solar panel assembly 12 to the energy storage device 16 is referred to as a charging function, whereas coupling the solar panel assembly 12 to a preconditioning device, such as the motor 18, is referred to as a preconditioning function.

[0013] The preconditioning mode includes applying energy to a preconditioning device to precondition (i.e., modify) a temperature of the passenger compartment or a component of the vehicle. For example, a passenger compartment of a vehicle may be preconditioned (e.g., cooled) when parked using the engine 18, which is powered by electrical energy generated by the solar panel assembly 12 when certain conditions exist. Other preconditioning devices may include, but are not limited to, a preheating device, such as an engine block heater or a three-way catalyst.

[0014] The charging function includes charging the energy storage device 16 using electrical energy generated by the solar panel assembly 12 when other predetermined conditions exist. When the vehicle is parked and solar energy is generated by the solar panel assembly 16, the charging function can be activated.

[0015] The processor 20 regulates the position of the switch 24 based on a plurality of conditions. The plurality of conditions include, but are not limited to, the vehicle status (e.g., driving or parked), solar energy availability, battery voltage, and a temperature difference between the vehicle's passenger compartment temperature and the outside ambient temperature. The processor 20 also monitors the load requirements of various vehicle components. Based on the load requirements, the processor 20 may actuate a switch 28 to supply power from the energy storage device 16 to the motor 18. The processor 20 may also actuate a switch 30 to distribute power from the energy storage device 16 to a preconditioning unit 31.When the loads are at a demand level where neither the energy from the solar panel assembly 12 nor the energy storage device 16 individually can provide a sufficient amount of power to one or more vehicle components, such as the blower motor, the energy from the solar panel assembly 12 and the energy storage device 16 may be used together to power the one or more of the vehicle components.

[0016] The vehicle power distribution system 11 further includes an electric vehicle battery high-voltage energy storage device 32. The high-voltage energy storage device 32 is coupled to an external source to receive high-voltage energy from an external source. The high-voltage energy storage device 32 is coupled to an auxiliary power module 34 that converts the high voltage received by the high-voltage storage device 32 into a low-voltage power supply. The auxiliary power module (APM) 34 is coupled to the energy storage device 16 and the high-voltage energy storage device 32. The APM 34 operates like an alternator in a conventional vehicle. The APM provides power flow between the high-voltage DC bus (HV-DC bus) and the low-voltage DC bus (LV-DC bus) of the vehicle.The APM-LV interface is connected to the vehicle's LV DC bus along with a low-voltage battery.

[0017] The high-voltage energy storage device 32 receives energy from multiple energy sources, including, but not limited to, an external power grid 36, a home source 38, and the in-vehicle renewable energy source 12. The external power grid 36 includes electrical energy received from a utility source, such as a power company, which generates the electricity and distributes it to homes and businesses. The external power grid 36 is coupled to the high-voltage storage device 32 via an AC / DC converter 42.

[0018] The home energy source 38 includes alternative renewable sources generated at or near a home or at another location where a vehicle can be charged. The home energy source 38 includes, but is not limited to, off-vehicle solar panels, wind turbines, and stored energy. The energy absorbed by the home energy source is coupled to a home energy management system 44, where the energy is used for household purposes or stored in a household home energy storage device 46. The home energy management system 44 can be coupled to the vehicle high energy storage device 32 to selectively transfer energy from the home energy storage device 46 to the vehicle high energy storage device 32.

[0019] The on-board renewable energy source 12 may include a solar panel array, natural gas, and another renewable energy source integrated as part of the vehicle. The on-board renewable energy source 12 is coupled to the high-voltage storage device 32 via a DC-DC converter 48 to provide energy captured by the solar panel array 12 to the high-voltage storage device 32.

[0020] The personalized electric vehicle charging management configuration is identified by a user of the vehicle via an interface application 50, which is a smartphone. The smartphone 50 communicates with the vehicle via a vehicle communication module 52. The vehicle communication module 52 provides a communication link for sending and receiving messages and data between the vehicle and other remote entities or devices. The vehicle communication module 52 further communicates with the service provider 54. The service provider 54 may be a membership-based communication service, such as OnStar®, currently provided with vehicles by vehicle manufacturers. This service is used to provide services such as, but not limited to, in-vehicle security, remote diagnostic systems, and turn-by-turn navigation over a wireless communication system.Remote services, such as OnStar®, include sufficient computing resources with processing power and large memory capacity to execute statistical and analytical routines of system 10. Using a remote system, as compared to an in-vehicle system, eliminates additional hardware and software that would otherwise be required in each vehicle for a vehicle-based system. However, in alternative embodiments, service provider 54 may be an in-vehicle module.

[0021] The service provider 54 captures the user inputs, monitors the vehicle energy storage conditions, obtains the vehicle energy storage status conditions, and obtains other remote data to recommend a charging strategy. The user uses a smartphone 50 or similar device to enter necessary information regarding the schedules for the day, as well as which charging priorities (hereinafter referred to as indices) are important to the user (e.g., cost-based, time-based, or green charging). The schedules for the day may include a specific destination or route, or may include a typical weekday or weekend trip commonly taken by the user. Other information that may be used includes departure times and the length of the trip. As described, the user can identify the importance of each index.The importance of each index can be classified as high, medium, or low. Alternatively, any other rating system can be used.

[0022] The vehicle energy storage status is used to make an informed decision regarding the recommended charging strategy. Such information may include the current level of energy generation from available sources, the available charging voltage (e.g., 120 V or 240 V), the current energy storage device charge level, the state of health (or operational state), the current vehicle loads, or the estimated vehicle loads used during the trip (e.g., heating, air conditioning, lighting, currently connected chargers).

[0023] Cloud computing data 56 relating to various information influencing charging strategies is obtained by the smartphone 50 and sent to the service provider 54. The cloud data 56 includes data relating to grid electricity, vehicle fuel information, electric charging stations, and weather information. The grid electricity information includes electricity usage and distribution rates and a real-time green index. The vehicle fuel information includes prices related to local gas stations, including those gas stations frequently visited by the user. Electric charging stations include the location and price of charging stations along the route or nearby. The weather information provides details such as the available sunlight in the area for capturing solar energy from a solar panel array. The cloud data 56 may be obtained from one or more information gathering sources.Examples of information gathering sources may include a web-based source, a weather station, or energy company or web data service provider.

[0024] Once the necessary information has been obtained, the service provider 54 analyzes all data from the various sources and provides a prioritized recommendation regarding the charging strategy. Various user preferences can be used. The following are some examples of user preferences and the prioritized recommendation generated by the service provider based on parameter data received by the service provider: Status Priority 1: Time-based (time = high, cost = medium, GI = low) - Charging time: 3 hours - Top-up costs: $0.50 - Charging green index: % Status Priority 2: Cost-based (time = medium, cost = high, GI = medium) - Charging time: 4 hours - Top-up costs: $0.35 - Charging green index: % Status Priority 3: based on green index (time = low, cost = medium, GI = high) - Charging time: 6 h - Top-up costs: $0.30 - Recharge green index: %%%

[0025] The service provider 54 may maintain vehicle-specific information for a vehicle so that the vehicle-specific information may be used to determine the charging strategy for the vehicle. For example, the service provider 54 may maintain the vehicle identification number (VIN) and related data for that vehicle. The related data may include, but is not limited to, a charging history, a battery history, and a driving history. The charging history may include an average charging time, an average time of day for refueling, or typical fueling levels. The battery history may include the current charge of the battery, the battery state of charge, the battery health, and the battery temperature. The driving history may include the average driving time and duration and the average driving distance.Service provider 54 may maintain and update the related data as part of a typical vehicle monitoring operation. The data may be collected from data monitoring modules in the vehicle, such as the powertrain control module, the battery control module, the vehicle monitoring control module, or other related modules.

[0026] The service provider 54 acts as an integrator, collecting the information and executing routines to determine the charging strategy and output a recommended charging strategy to the user. The recommended charging strategy can be output via the user interface device 50 or another interface external or internal to the vehicle.

[0027] The following methodology describes the process for managing the personalized top-up management strategy.

[0028] The program is initiated in block 60. The program starts when the vehicle's ignition switch is turned on or by a user action.

[0029] In block 61, the service provider initiates an efficient charging algorithm, collecting data from various sources. The data is collected in blocks 62, 63, 64, and 65.

[0030] In block 62, vehicle charging / energy-related information is obtained. Such information may include the current level of energy generation available for power from the vehicle's solar panel array or any other on-vehicle renewable energy source. Other information may include whether the charging capability is 120V or 240V, the vehicle's location relative to refueling stations, the battery state of charge (SOC), and the current vehicle loads currently operating on the vehicle. Further, the load and other information may be used to determine whether the vehicle can make it to a next destination without refueling before departure.

[0031] In block 63, a determination is made regarding the utility plan of a user associated with the utility company. Such information may include the type of utility, the rates and rates for a particular time of day, and the maximum allowable energy flow rate.

[0032] In block 64, the user submits / enters their schedules for the day via a smartphone, home energy management system, or website. The user can enter a typical schedule that is usually run on a weekday or weekend basis, or can enter a specific schedule.

[0033] In block 65, the driver selects one of the index options. The index options include a time-based index, a cost-based index, a green index-based option, or a combination. The time-based option includes departure based on the urgency of charging the vehicle (e.g., if the user plans an earlier-than-usual departure time). The cost-based index is based on whether the user desires the most economical cost to charge the vehicle. The green index-based option includes the charging provider with the smallest carbon footprint or the highest green index.

[0034] In block 66, home energy-related information is provided to a home energy management system or via a website or other long-range communications network. The home energy-related information includes information related to a current level of energy production from available resources. Such resources include home-based resources, wind-based resources, a vehicle-based resource, or another renewable energy-based resource.

[0035] In block 67, the information from blocks 62 - 66 is delivered to the service provider or similar to calculate a charging strategy.

[0036] In block 68, the vehicle's energy demand is estimated based on the following data, which includes, but is not limited to, expected driving distance, battery SOC, weather conditions, traffic, schedules, driving style, and map data.

[0037] In step 69, the optimal energy source for the user is determined based on the user's preferences regarding energy cost, charging time, and green index.

[0038] In step 70, the determined charging strategy is provided to the user for approval.

[0039] In step 71, it is determined whether the user accepts the determined charging strategy. If it is determined that the user has accepted the charging strategy, the vehicle is programmed to charge using the selected charging strategy in step 72. If the user does not accept the charging strategy, the process returns to step 61.

[0040] While certain embodiments of the present invention have been described in detail, those skilled in the art to which this invention pertains will recognize various alternative designs and embodiments for practicing the invention as defined by the following claims.

Claims

[1] Configurable energy management system (10) for charging an electric vehicle, comprising: an energy storage device (16) for storing energy; an on-vehicle regenerative energy source (12) for generating electrical energy for charging the on-vehicle energy storage device (16); at least one source of renewable energy external to the vehicle for providing electrical energy to the vehicle for charging the on-vehicle energy storage device (16); a vehicle communication module (52) for transmitting and receiving data; an integration module for integrating in-vehicle energy parameter data, in-vehicle renewable energy parameter data, off-vehicle renewable energy parameter data, user parameter data, web-based data, and cloud computing data (56), wherein the cloud computing data (56) is obtained from at least one information retrieval source and includes data related to grid electricity, vehicle fuel information, electric charging stations, and weather information; and a user interface device (50) for communicating with the vehicle communication module (52) and the integration module, wherein the user interface device (50) is a smartphone and transmits the user parameter data to the integration module, wherein the user parameter data comprises a prioritization of preferred parameters for charging the in-vehicle energy storage device (16), wherein the preferred parameters comprise a time-based index and / or a cost-based index and / or a green index; wherein the integration module identifies an optimal energy source for charging the vehicle based on the on-vehicle energy parameter data, the on-vehicle renewable energy parameter data, the off-vehicle renewable energy parameter data, the user parameter data, the web-based data, and the cloud computing data (56), wherein the cloud computing data (56) is obtained by the smartphone and sent to the integration module. [2] The configurable energy management system (10) of claim 1, wherein the integration module is a remote service provider that communicates with the vehicle via the vehicle communication module (52), the service provider having computing devices with computing power and large memory capacity for executing statistical and analytical routines for determining the prioritization of preferred parameters. [3] The configurable energy management system (10) of claim 2, wherein the service provider comprises a database for maintaining sets of respective parameter data for each monitored vehicle. [4] The configurable energy management system (10) of claim 3, wherein the remote service provider monitors a plurality of vehicle operations, the plurality of vehicle operations being used in determining the prioritization of preference parameters. [5] The configurable energy management system (10) of claim 1, wherein the at least one source of renewable energy external to the vehicle comprises electrical energy from an energy utility service provider. [6] The configurable energy management system (10) of claim 1, wherein the at least one off-vehicle renewable energy source comprises a home solar energy generation system. [7] The configurable energy management system (10) of claim 1, wherein the at least one off-vehicle renewable energy source comprises a home wind turbine generation system. [8] Configurable energy management system (10) according to claim 1, wherein the on-vehicle energy parameter data comprises an available charging voltage and / or a state of charge of a vehicle battery and / or activated vehicle electrical loads. [9] The configurable energy management system (10) of claim 1, wherein the user parameter data further comprises a planned driving route identified by a user.

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