A charging control method and system for an extended-range electric vehicle and an electric vehicle

Abstract

A charging control method, system and electric vehicle for an extended-range electric vehicle, wherein a first threshold and a second threshold are preset, and the first threshold is greater than the second threshold; the control method steps are as follows: 1) when the battery power is lower than the first threshold and higher than the second threshold, proceed to step 2); when the battery power is lower than the second threshold, the controller controls the battery to be forced to charge; 2) the controller determines whether P is satisfied v +Pb1>P u , P v , Pb1 and P u The current vehicle driving power requirement, the battery minimum charging power requirement and the maximum power value of the engine's high-efficiency operating range are respectively. If not, it is the best time to charge, and the engine is controlled to increase the power to P u , the battery is charged with power P u ‑P v If yes, charging is not performed and the process goes to step 3); 3) the best charging time is predicted according to the terrain or road conditions ahead, and charging is performed at the best charging time; 4) the process goes back to step 1). The present invention predicts the best charging time for the extended-range electric vehicle, ensuring that the engine operates in a high-efficiency power range when charging the battery, thereby achieving better economy.

Description

Technical Field

[0001] The present invention relates to the field of electric vehicles, and in particular to a charging control method and system for an extended-range electric vehicle and an electric vehicle. Background Art

[0002] At present, the energy management strategies adopted by extended-range electric vehicles (REEV) include switch type, segmented type and power following type. Among them, the power following method greatly reduces the charging and discharging process. In a certain power range of engine high efficiency, the power generated by the engine driving the generator directly drives the motor, so the engine power is always approximately equal to the driving power required for vehicle driving; when the driving power required by the vehicle is very low, the engine works at the lowest power point of the pre-set high efficiency range, and the excess power is used to charge the battery; when the driving power is very large and the highest power of the engine high energy efficiency range is insufficient, the battery is discharged to supplement.

[0003] This power following method ensures that the engine can operate in a high-efficiency power range for a long time, but this method cannot ensure that the battery SOC can be maintained in a certain range. Usually, some auxiliary strategies need to be added to force charging when the battery SOC is low. Forced charging may cause the engine to operate beyond the high-efficiency power range. Therefore, traditional power following energy management may increase energy consumption if the timing of battery charging is improperly selected. Summary of the invention

[0004] The main purpose of the present invention is to overcome the above-mentioned defects in the prior art and to propose a charging control method, system and electric vehicle for an extended-range electric vehicle, so as to reduce the proportion of time that the engine runs in a non-high energy efficiency range in order to charge the battery, thereby having better economy.

[0005] The present invention adopts the following technical solution:

[0006] A charging control method for an extended-range electric vehicle is characterized in that: a first threshold and a second threshold are preset, and the first threshold is greater than the second threshold; the control method steps are as follows:

[0007] 1) When the battery power is lower than the first threshold and higher than the second threshold, proceed to step 2); when the battery power is lower than the second threshold, the controller controls the battery to be forced to charge;

[0008] 2) The controller determines whether P is satisfied v +Pb1>P u , P v , Pb1 and P u The current vehicle driving power requirement, the battery minimum charging power requirement and the maximum power value of the engine's high-efficiency operating range are respectively. If not, it is the best time to charge, and the engine is controlled to increase the power to P u, the battery is charged with power P u -P v Charge-charge; if yes, do not charge and go to step 3);

[0009] 3) Predict the best charging time based on the terrain or road conditions ahead, and charge at the best charging time;

[0010] 4) Return to step 1).

[0011] Preferably, in step 3), the power demand P′ of the vehicle driving in the front terrain or road environment is predicted v , determine whether P′ is satisfied v +Pb1>P u , if not, the vehicle reaches the road ahead and satisfies P′ v +Pb1<P u When the battery is fully charged, it is the best time to charge and charging starts; otherwise, charging does not start.

[0012] Preferably, in step 3), if the best charging opportunity does not appear in the front terrain or road environment, and the battery power is lower than the second threshold, the battery is controlled to be forcibly charged to the first threshold.

[0013] Preferably, if the terrain or road environment ahead has a slope change, the power prediction demand P′ v The estimation method is as follows:

[0014] 1) Read the current engine load percentage value N, where N is the current power as a percentage of the engine's maximum power W max The current slope value θ0 and the forward slope value θ are obtained from the electronic horizon. i ;

[0015] 2) Assuming that the vehicle maintains a similar state, that is, the speed is V, then the slope ahead is θ i The predicted load percentage of the engine is N' i , calculate the power forecast demand P′ v =N′ i W max .

[0016] Preferably, the change in traction force due to the slope is: F s =mgsin(θ i -θ0)≈mg(θ i -θ0);

[0017] Power change: P = mgV(θ i -θ0);

[0018] The predicted load percentage of the engine is: N' i=N+mgV(θ i -θ0) / W max ;

[0019] Among them, m is the mass of the vehicle and g is the acceleration due to gravity.

[0020] Preferably, if there is a speed limit change in the terrain or road environment ahead, the speed limit information of point j ahead obtained from the electronic horizon becomes V j , then the vehicle speed is replaced by V j , then the corresponding predicted load percentage N' j For: N' j =N+mgV j (θ i -θ0) / W max , power forecast demand P′ v =N' j W max .

[0021] Preferably, if there is curve information in the front terrain or road environment, the turning radius of the front k point obtained from the electronic horizon is R k and the turning angle is a k ,but

[0022] The ideal turning resistance coefficient f r is: f r =(V 2 / Rg)a

[0023] The power increase due to the curve is:

[0024] The total power increase is:

[0025]

[0026] The power forecast demand is P′ v =N′ k W max ;

[0027] Where R is the turning radius and a is the turning angle.

[0028] A charging control system for an extended-range electric vehicle comprises an engine, a generator, a motor, a battery and a controller; the generator is connected to the motor, the battery and the engine, and the controller is connected to the engine and the generator; the controller is characterized in that: the controller is also connected to an electronic horizon system to obtain the terrain or road environment in front of the vehicle, and adopts the above-mentioned charging control method for an extended-range electric vehicle to control the engine to drive the generator to charge the battery.

[0029] An extended-range electric vehicle includes a vehicle body, and is characterized in that it also includes the above-mentioned charging control system of the extended-range electric vehicle.

[0030] It can be seen from the above description of the present invention that, compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. The method, system and electric vehicle of the present invention can combine electronic horizon information to predict the best charging time for the extended-range electric vehicle (REEV), ensuring that the engine operates in a high-efficiency power range when charging the battery, thereby achieving better economy.

[0032] 2. The method, system and electric vehicle of the present invention can directly determine the optimal charging time based on the current vehicle driving power demand, the battery's minimum charging power demand and the maximum power value of the engine's high-efficiency operating range, or predict the optimal charging time in combination with the predicted power demand of the vehicle driving in the front terrain or road environment, thereby achieving optimal energy management.

[0033] 3. The method, system and electric vehicle of the present invention can calculate the power prediction demand based on the acquired information on changes in the terrain or road environment ahead, including changes in slope, speed limit and curve, so as to predict the best charging time for different road conditions.

[0034] 4. The method, system and electric vehicle of the present invention can also be expanded according to actual conditions. That is, if the road information ahead that can be provided by the electronic horizon involves other factors that change the vehicle power demand, the corresponding power prediction demand can be calculated based on the impact of the factor on the power. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a structural block diagram of the extended-range electric vehicle of the present invention;

[0036] Figure 2 is the speed limit V from the electronic horizon system in the present invention j With slope θ i Relationship diagram;

[0037] Figure 3 is the speed limit V from the electronic horizon system in the present invention j , slope θ i , the relationship diagram between turning radius and bending angle.

[0038] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. DETAILED DESCRIPTION

[0039] The present invention is further described below through specific implementation modes.

[0040] See also Figure 1A charging control system for an extended-range electric vehicle is provided with a controller, an engine, a generator, a motor and a battery, etc. The generator is connected to the motor and the battery, and the motor is used to drive the reducer or the differential to work. The controller, namely the APU, is connected to the engine and the generator, and controls the engine to drive the generator to generate power to directly drive the motor, or controls the engine to drive the generator to charge the battery. The controller is also connected to the electronic horizon system, and is used to obtain the terrain or road environment in front of the vehicle from the electronic horizon system. According to the predicted conditions of the terrain ahead, the controller adopts a charging control method of an extended-range electric vehicle of the present invention to predictively control the charging of the remaining power SOC of the battery, which can ensure to a greater extent that the engine operates in a high-efficiency power range even when charging the battery.

[0041] The electronic horizon in the present invention includes map data, GPS / Beidou positioning and forward search engine, etc., and is characterized in that the vehicle's positioning latitude and longitude and the vehicle's forward direction information are parsed according to the GPS / Beidou satellite positioning system, and the geographical information in front of the vehicle is searched on the electronic horizon map, and the geographical information in front is transmitted to the controller through the CAN bus or Ethernet bus. The information needed by this system includes terrain or road environment information such as slope information, curve information, speed limit information, etc. that are closely related to changes in vehicle power demand.

[0042] A charging control method for an extended-range electric vehicle of the present invention presets a first threshold and a second threshold, wherein the first threshold is an optional charging threshold, and the second threshold is a forced charging threshold, and the first threshold is greater than the second threshold. The selection of the first threshold and the second threshold can be set as needed without limitation.

[0043] The control method steps are as follows:

[0044] 1) When the controller detects that the battery power is lower than the first threshold and higher than the second threshold, the controller does not immediately increase the engine power to charge the battery, but enters step 2); when the battery power is lower than the second threshold, the controller controls the battery to be forced charged.

[0045] 2) Determine whether P is satisfied v +Pb1>P u , P v , Pb1 and P u The current vehicle driving power requirement, the battery minimum charging power requirement and the maximum power value of the engine's high-efficiency operating range are respectively. If not, it is the best time to charge, and the engine is controlled to increase the power to P u , the battery is charged with power P u -P v If yes, do not charge and go to step 3).

[0046] 3) Predict the best charging time based on the terrain or road conditions ahead, and charge at the best charging time.

[0047] 4) Return to step 1).

[0048] Among them, in step 3), predicting the best charging time specifically includes: predicting the power demand P′ of the vehicle driving in the front terrain or road environment v , determine whether P′ is satisfied v +Pb1>P u , if not, the vehicle reaches the road ahead and satisfies P′ v +Pb1<P u When the time is right, it is the best time to charge, and charging starts; otherwise, charging does not start;

[0049] In the process of predicting the best charging time in step 3), if the best charging time does not appear in the front terrain or road environment, and the battery power is lower than the second threshold, the battery is forced to be charged until the battery SOC reaches the first threshold.

[0050] The power prediction calculation of the present invention is derived from the vehicle power stability formula. If the terrain or road environment ahead has a slope change, the power prediction requirement P′ v The estimation method is as follows:

[0051] 1) Read the current engine load percentage value N, where N is the current power as a percentage of the engine's maximum power W max The current slope value θ0 and the forward slope value θ are obtained from the electronic horizon. i ;

[0052] 2) Assuming that the vehicle maintains a similar state, that is, the speed is basically stable at V, then the slope ahead is θ i The predicted load percentage of the engine is N' i , calculate the power forecast demand P′ v =N′ i W max .

[0053] The change in traction due to slope is: F s =mgsin(θ i -θ0)≈mg(θ i -θ0);

[0054] Power change: P = mgV(θ i -θ0);

[0055] The predicted load percentage of the engine is: N' i =N+mgV(θ i -θ0) / Wmax ;

[0056] Where m is the mass of the vehicle and g is the acceleration due to gravity.

[0057] For further information, see Figure 2 If the terrain or road environment ahead has a speed limit change in addition to the slope change, the speed limit information of point j ahead obtained from the electronic horizon becomes V j , then when reaching point j, the speed is V j , then the corresponding predicted load percentage N' j For: N' j =N+mgV j (θ i -θ0) / W max , power forecast demand P′ v =N' j W max .

[0058] For further information, see Figure 3 , if there is also curve information in the front terrain or road environment, the turning radius of the front k point obtained from the electronic horizon is R k and the turning angle is a k ,but

[0059] The ideal turning resistance coefficient f r is: f r =(V 2 / Rg)a

[0060] The power increase due to the curve is:

[0061] The total power increase is:

[0062]

[0063] The power forecast demand is P′ v =N′ k W max ;

[0064] Where R is the turning radius and a is the turning angle.

[0065] In practical applications, the present invention can be further expanded according to actual conditions. That is, if the road information ahead that can be provided by the electronic horizon involves other factors that change the vehicle power demand, the corresponding power prediction demand can be calculated through a public, well-known, axiomatic formula for the impact of this factor on power.

[0066] See also Figure 1The present invention also proposes an extended-range electric vehicle, including a vehicle body and the above-mentioned charging control system of the extended-range electric vehicle. The charging control system of the extended-range electric vehicle adopts the charging control method of the extended-range electric vehicle of the present invention to control the generator to drive the generator to charge the battery, ensuring that the engine operates in a high-efficiency power range when charging the battery, and has better economy.

[0067] The method and device of the present invention can predict the reasonable charging time for the extended-range electric vehicle (REEV) based on the electronic horizon information, reduce the proportion of time that the engine runs in a non-high-efficiency range to charge the battery, and have better economy.

[0068] The above is only a specific implementation of the present invention, but the design concept of the present invention is not limited thereto. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. A charging control method for an extended-range electric vehicle, characterized in that: A first threshold and a second threshold are preset, and the first threshold is greater than the second threshold; the control method steps are as follows: 1) When the battery power is lower than the first threshold and higher than the second threshold, proceed to step 2); when the battery power is lower than the second threshold, the controller controls the battery to be forced to charge; 2) The controller determines whether P is satisfied v +Pb1>P u , P v , Pb1 and P u The current vehicle driving power requirement, the battery minimum charging power requirement and the maximum power value of the engine's high-efficiency operating range are respectively. If not, it is the best time to charge, and the engine is controlled to increase the power to P u , the battery is charged with power P u -P v If yes, do not charge and go to step 3); 3) Predict the best charging time based on the terrain or road conditions ahead, and charge at the best charging time; Predict the power demand P of the vehicle driving in the front terrain or road environment v ', determine whether P is satisfied v '+Pb1>P u , if not, the vehicle reaches the road ahead and satisfies P v '+Pb1<P u When the best charging time comes, charging starts; otherwise, charging does not start; if the best charging time does not appear in the terrain or road environment ahead, and the battery power is lower than the second threshold, the battery is forced to be charged to the first threshold; 4) Return to step 1).

2. A charging control method for an extended-range electric vehicle as claimed in claim 1, characterized in that: If the terrain or road environment ahead has a slope change, the power prediction demand P v The estimation method is as follows: 1) Read the current engine load percentage value N, where N is the current power as a percentage of the engine's maximum power W max The current slope value θ0 and the forward slope value θ are obtained from the electronic horizon. i ; 2) Assuming that the vehicle maintains a similar state, that is, the speed is V, then the slope ahead is θ i The predicted load percentage of the engine is N' i , calculate the power forecast demand P′ v =N′ i W max .

3. A charging control method for an extended-range electric vehicle as claimed in claim 2, characterized in that: The change in traction due to slope is: F s =mgsin(θ i -θ0)≈mg(θ i -θ0); Power change: P = mgV(θ i -θ0); The predicted load percentage of the engine is: N i '=N+mgV(θ i -θ0) / W max ; Among them, m is the mass of the vehicle and g is the acceleration due to gravity.

4. The charging control method for an extended-range electric vehicle according to claim 1, characterized in that: If the speed limit changes in the terrain or road environment ahead, the speed limit information of point j ahead is obtained from the electronic horizon and becomes V j , then the vehicle speed is replaced by V j , then the corresponding predicted load percentage N' j For: N' j =N+mgV j (θ i -θ0) / W max , power forecast demand P v '=N' j W max .

5. The charging control method for an extended-range electric vehicle according to claim 1, characterized in that: If there is curve information in the front terrain or road environment, the turning radius of the front k point obtained from the electronic horizon is R k and the turning angle is a k , then the ideal turning resistance coefficient f r is: f r =(V 2 / Rg)a The power increase due to the curve is: The total power increase is: The power forecast demand is P′ v =N′ k W max ; Among them, R is the turning radius and a is the turning angle.

6. A charging control system for an extended-range electric vehicle, comprising an engine, a generator, a motor, a battery and a controller; the generator is connected to the motor, the battery and the engine, and the controller is connected to the engine and the generator; characterized in that: The controller is also connected to the electronic horizon system to obtain the terrain or road environment in front of the vehicle, and adopts a charging control method for an extended-range electric vehicle as described in any one of claims 1 to 5 to control the engine to drive the generator to charge the battery.

7. An extended-range electric vehicle, comprising a vehicle body, characterized in that: It also includes a charging control system for an extended-range electric vehicle as claimed in claim 6.

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