CN113311324A - New energy automobile relay on-line detection method, battery management system and battery pack - Google Patents
New energy automobile relay on-line detection method, battery management system and battery pack Download PDFInfo
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/005—Testing of electric installations on transport means
- G01R31/006—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks
Abstract
The invention discloses a new energy automobile relay on-line detection method, a battery management system and a battery pack. Performed by a battery management system, the method comprising: detecting state parameters of the relay; determining the times of power on and power off and the times of faults of the relay according to the state parameters, and generating detection information; sending the detection information to a cloud analysis platform; the detection information is used for the cloud analysis platform to analyze according to the detection information to obtain pre-estimated data; and receiving pre-estimated data sent by the cloud analysis platform, wherein the pre-estimated data comprises the pre-estimated service life of the relay and the fault probability of the relay. The technical scheme provided by the embodiment of the invention realizes the acquisition and analysis of relay data parameters, and the relay fault is early warned by utilizing the analysis result, so that the problem in use of a user is avoided, and the use experience of the user is improved.
Description
Technical Field
The embodiment of the invention relates to a detection technology, in particular to a new energy automobile relay online detection method, a battery management system and a battery pack.
Background
The relay of the new energy automobile is a control element and a core element of the new energy automobile, and the failure of the relay directly causes the failure of the whole electric system. And therefore is particularly important for effective detection of the relay.
In the prior art, a method for detecting and monitoring the failure of a relay generally judges the failure reason of the relay according to the failure phenomenon and the influence after the failure of the relay, and then carries out fault maintenance. This also greatly affects the user's trip, and brings inconvenience to the user.
Disclosure of Invention
The invention provides a new energy automobile relay on-line detection method, a battery management system and a battery pack, which realize relay data parameter acquisition and analysis, and can early warn a relay fault in advance by using an analysis result, so that a user is guided to maintain or replace the relay, the condition that the relay fault occurs in the using process of the user can be reduced, and the using experience of the user is improved.
In a first aspect, an embodiment of the present invention provides a new energy automobile relay online detection method, which is executed by a battery management system, and the method includes:
detecting state parameters of the relay;
determining the times of power on and power off and the times of faults of the relay according to the state parameters, and generating detection information;
sending the detection information to a cloud analysis platform; the detection information is used for the cloud analysis platform to analyze according to the detection information to obtain pre-estimated data;
and receiving pre-estimated data sent by the cloud analysis platform, wherein the pre-estimated data comprises the pre-estimated service life of the relay and the fault probability of the relay.
Optionally, determining the number of times of powering on and powering off the relay according to the state parameter includes:
when a relay closing instruction of the new energy automobile is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; and if the opening and closing functional state of the relay and the currents at the two high-voltage ends of the relay are normal, controlling the relay to be closed and normally electrified, and recording after accumulating the times of normally electrified relay for 1 time.
Optionally, determining the number of times of powering on and powering off the relay according to the state parameter includes: when the new energy automobile relay opening instruction is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; and if the relay opening and closing function state and the currents at the two high-voltage ends of the relay are normal, controlling the relay to be normally powered off, and recording after accumulating the times of normally powering off the relay for 1 time.
Optionally, determining the number of times of powering on and powering off the relay according to the state parameter includes: when a relay closing instruction of the new energy automobile is received, judging the on-off function state of the relay and the current of the two high-voltage ends of the relay according to the state parameters; and if the state of the relay opening and closing function is judged to be normal, the current at the two high-voltage ends of the relay is abnormal, and the relay is controlled to be closed and electrified if the relay is allowed to be closed, and the times of abnormal electrification of the relay are accumulated for 1 time and then recorded.
Optionally, determining the number of times of powering on and powering off the relay according to the state parameter includes: when the new energy automobile relay opening instruction is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; if the relay is judged to be in a normal opening and closing functional state, the currents at the two high-voltage ends of the relay are abnormal, but the relay is controlled to be opened and powered off if the relay is allowed to be closed, and the times of abnormal power off of the relay are accumulated for 1 time and then recorded.
Optionally, determining the number of times of the fault of the relay according to the state parameter includes:
when a relay closing instruction of the new energy automobile is received, judging the state of the relay opening and closing function according to the state parameters; and if the open/close functional state fault of the relay is judged, accumulating the times of the power-on fault of the relay for 1 time and then recording.
Optionally, determining the number of times of the fault of the relay according to the state parameter includes: when the new energy automobile relay disconnection instruction is received, judging the relay on-off function state according to the state parameters; and if the open/close functional state fault of the relay is judged, accumulating the times of the power-off fault of the relay for 1 time and then recording.
In a second aspect, an embodiment of the present invention provides a battery management system, where the battery management system includes a data detection unit;
the data detection unit is used for detecting state parameters of the relay, determining the times of power-on and power-off of the relay and the times of faults according to the state parameters, and generating detection information;
the data detection unit is further used for sending the detection information to a cloud analysis platform and receiving pre-estimated data sent by the cloud analysis platform; the detection information is used for the cloud analysis platform to analyze according to the detection information to obtain pre-estimated data; the estimated data comprises the estimated service life of the relay and the fault probability of the relay.
Optionally, the battery management system further includes a data storage unit;
the data storage unit is connected with the data detection unit and is used for storing the detection information and the pre-estimation data.
In a third aspect, an embodiment of the present invention provides a battery pack, including any one of the battery management systems.
According to the technical scheme provided by the embodiment of the invention, the estimated residual life of the relay and the probability of the fault of the relay are obtained by detecting the state parameters of the relay, the power-on and power-off times and the fault times of the relay, the data parameter acquisition and analysis of the relay are realized, and the fault of the relay is early warned by using the analysis result, so that a user is guided to maintain or replace the relay, the condition that the relay fault occurs in the using process of the user is reduced, and the use experience of the user is improved.
Drawings
Fig. 1 is a schematic structural diagram of an online detection system for a new energy vehicle relay according to an embodiment of the invention.
Fig. 2 is a schematic diagram of an electrical lifetime curve according to an embodiment of the present invention.
Fig. 3 is a schematic flow chart of an online detection method for a new energy automobile relay, provided by an embodiment of the invention.
Fig. 4 is a schematic diagram of a power-on process of an on-line detection method for a new energy vehicle relay according to an embodiment of the present invention.
Fig. 5 is a schematic power-off flow diagram of an on-line detection method for a new energy vehicle relay according to an embodiment of the invention.
Fig. 6 is a schematic flow chart of another new energy vehicle relay on-line detection method provided by the embodiment of the invention.
Fig. 7 is a schematic structural diagram of a battery management system according to an embodiment of the present invention.
Fig. 8 is a schematic structural diagram of another battery management system according to an embodiment of the present invention.
Fig. 9 is a schematic structural diagram of an online detection system for a new energy vehicle relay according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The new energy automobile relay is a control element and a core element of the new energy automobile, and the failure of the relay directly causes the failure of the whole electric system. The method for detecting the failure of the relay mainly judges the failure reason of the relay according to the influence performance of the failure of the relay, and belongs to the detection after the failure occurs. Even if the fault cause is detected after the fault occurs, the vehicle has the fault, and the use experience of a user is influenced.
In view of this, an embodiment of the present invention provides an online detection system for a new energy vehicle relay, and fig. 1 is a schematic diagram of a structure of the online detection system for the new energy vehicle relay, which is provided in the embodiment of the present invention, and is shown in fig. 1, where the system includes a cloud analysis platform 120 and a battery management system 220;
the battery management system 220 is configured to detect a state parameter of the relay, determine the number of times of power up and power down and the number of times of faults of the relay according to the state parameter, and send the state parameter, the number of times of power up and power down and the number of times of faults to the cloud analysis platform 120;
the cloud analysis platform 120 is connected to the battery management system 220, and the cloud analysis platform 120 is configured to obtain the estimated service life of the relay and the failure probability of the relay according to the state parameters, the power-on and power-off times and the failure times.
Specifically, the state parameters of the relay include at least one of current at two high-voltage ends of the relay, current at two low-voltage ends of the relay, working temperature of the relay, voltage at two high-voltage ends of the relay, voltage at two low-voltage ends of the relay, whether the relay is in fault or not and on or off state of the relay; the battery management system 220 judges whether the state of the relay is normal, abnormal or fault according to the state parameters of the relay, thereby determining and recording the times of normal power-on and power-off, the times of abnormal power-on and power-off and the times of fault of the relay. And sending the state parameters, the power-on and power-off times and the failure times to the cloud analysis platform 120, and estimating the estimated service life of the relay and the failure probability of the relay by the cloud analysis platform 120 according to the state parameters, the power-on and power-off times and the failure times by using a failure model. Fig. 2 is a schematic diagram of an electrical lifetime curve according to an embodiment of the present invention, and referring to fig. 2, the electrical lifetime curve is a relationship curve between an equivalent switching frequency and a switching current. The estimated service life of the relay is predicted according to the electrical wear of the contact in the working process of the relay, namely when the accumulated electrical wear of the contact reaches the maximum allowable wear, the service life of the relay is considered to be terminated.
The expression of the electrical wear amount obtained from the electrical life curve is:
in the formula: n is the number of times of disconnection; ib is an effective value Ib of the contact opening current; a is an index of the effective value of the breaking current, depending on the contact material.
The expression for remaining life is:
in the formula: l is the residual life of the relay; qyIs a characteristic of the maximum allowable total amount of electrical wear; q is the electrical wear amount.
When the relay is closed, the voltage Ub at the high-voltage end of the relay can be measured by the battery management system 220, and then the effective value Ib of the contact opening current is equal to Ub/r, where r is the internal resistance at the load end of the relay.
Due to the large error in the application of the electrical life curve. An electric quantity abrasion model is constructed by an engineering improvement electric quantity abrasion calculation method, and the expression of the electric quantity abrasion model is as follows:
in the formula: i.e. ibiThe current of the i-th breaking is obtained; i.e. i1i，i2i，i3iThe three-phase current of the breaker at the ith breaking time is respectively; t is taiThe arcing time at the ith breaking is the arcing time; t is ta1i，ta2i，ta3iAnd the arc burning time of the three phases of the circuit breaker in the ith breaking is respectively.
Meanwhile, the influence of the temperature environment on the relay is considered, and a degradation model of the relay along with the temperature is constructed on the basis of an Arrhenius model. The expression is as follows:
in the formula: m is a measured performance parameter value of the product at a part of time point in the working process; a. the0Is a positive coefficient; k is Boltzmann constant; t is the thermodynamic temperature; Δ E is activation energy.
The expression for optimizing the electrical wear amount can be obtained based on the above calculation as follows:
in the formula: n is the number of times of disconnection; ib is an effective value Ib of the contact opening current; a is an index of the effective value of the breaking current and is related to the contact material; k is a parameter obtained by the electric grinding quantity model; and T is a parameter obtained by the temperature model.
The expression of the optimized remaining life is as follows:
in the formula: l is the residual life of the relay; qyIs a characteristic of the maximum allowable total amount of electrical wear; q is the electric abrasion loss when the circuit is disconnected; q is the amount of electrical wear when closed.
Based on the above calculation, through research of the inventor, it is found that as the remaining life decreases, the failure rate gradually increases, and through 2-fitting, a model of the remaining life and the failure rate can be obtained, and the expression is as follows:
in the formula: s is the fault probability; k and b are related to relay properties and are obtained by parameter fitting; and L is the residual service life of the relay.
Illustratively, the estimated life and failure probability calculation process for the relay closure is as follows: when the relay is closed, the battery management system collects the voltage Ub at the two high-voltage ends of the relay and acquires the accumulated closing times N. The effective value of the contact opening current is calculated according to the expression Ib ═ Ub/r. The relay closing may refer to the number of normal power-on times and the number of abnormal power-on times of the relay.
And substituting the effective value Ib of the contact opening current and the closing times N into the expression for optimizing the electric abrasion quantity to obtain the closed electric abrasion quantity Qclose. And obtaining the residual service life L of the relay according to the expression of the residual service life after the electric abrasion Q is substituted into the optimization. Wherein the Q-break in the equation is taken from the last stored Q-break data. And substituting the residual service life L into the model of the residual service life and the fault rate to obtain the calculated fault probability S of the relay.
Illustratively, the estimated life and failure probability calculation process for the relay closure is as follows: when the relay is disconnected, the battery management system collects an effective value Ib of the contact disconnection current before the relay is disconnected, and obtains accumulated disconnection times N, wherein the accumulated disconnection times can refer to the sum of the normal power-off times, the abnormal power-off times and the fault power-off times of the relay.
And substituting the effective value Ib of the contact opening current and the opening times N into the expression for optimizing the electrical wear amount to obtain the opened electrical wear amount Qoff. And obtaining the residual service life L of the relay according to the expression of the residual service life after the electric abrasion quantity Q is subjected to the replacement optimization. Wherein the Q-closure in the equation is taken from the last Q-closure data stored. And substituting the residual service life L into the model of the residual service life and the fault rate to obtain the calculated fault probability S of the relay.
The embodiment of the invention also provides a new energy automobile relay online detection method, and fig. 3 is a schematic flow diagram of the new energy automobile relay online detection method provided by the embodiment of the invention, the embodiment is applicable to a new energy automobile relay online detection scene, and is executed by a battery management system, referring to fig. 3, and the method comprises the following steps:
s110, detecting state parameters of a relay;
the state parameters of the relay comprise at least one of high-voltage two-end current of the relay, low-voltage two-end current of the relay, working temperature of the relay, high-voltage two-end voltage of the relay, low-voltage two-end voltage of the relay, whether the relay breaks down and the on or off state of the relay;
s120, determining the power-on and power-off times and the failure times of the relay according to the state parameters, and generating detection information;
specifically, the state of the relay is judged to be normal, abnormal or fault according to the state parameters of the relay, so that the times of normal power-on and power-off, the times of abnormal power-on and power-off and the times of fault of the relay are determined and recorded, and the detection information is generated.
S130, sending the detection information to a cloud analysis platform; the detection information is used for the cloud analysis platform to analyze according to the detection information to obtain pre-estimated data;
the detection information can be sent to the cloud analysis platform through wireless or wired communication.
S140, receiving the pre-estimated data sent by the cloud analysis platform, wherein the pre-estimated data comprises the pre-estimated service life of the relay and the fault probability of the relay.
Specifically, a user is reminded of maintenance or replacement of the relay according to the received estimated data.
According to the technical scheme provided by the embodiment of the invention, the estimated residual life of the relay and the probability of the fault of the relay are obtained by detecting the state parameters of the relay, the power-on and power-off times and the fault times of the relay, the data parameter acquisition and analysis of the relay are realized, and the fault of the relay is early warned by using the analysis result, so that a user is guided to maintain or replace the relay, the condition that the relay fault occurs in the using process of the user is reduced, and the use experience of the user is improved.
Optionally, determining the power-on and power-off times of the relay according to the state parameter includes:
when a relay closing instruction of the new energy automobile is received, judging the on-off function state of the relay and the current of the two high-voltage ends of the relay according to the state parameters; and if the opening and closing functional state of the relay and the currents at the two high-voltage ends of the relay are normal, controlling the relay to be closed and normally electrified, and accumulating the times of normally electrified relay for 1 time and then recording.
Specifically, the number of times of powering on and powering off the relay includes the number of times of normally powering on the relay and the number of times of normally powering off the relay. For example, when the vehicle is started or charged, the battery management system receives a command of closing the relay of the whole vehicle, and then the relay is closed. And a battery management system acquires state data before the relay is closed. The battery management system judges the functional state of the opening and closing of the relay according to the state data of the relay, if the functional state is normal, the current at the two high-voltage ends of the relay is judged, if the functional state is normal, the relay can be normally powered on, the battery management system controls the relay to be closed, and the battery management system records the normal power-on times of the relay for 1 time. And accumulating for 1 time every time the relay is normally electrified, so that the normal electrification times of the relay are counted.
Optionally, determining the power-on and power-off times of the relay according to the state parameter includes: when a new energy automobile opening relay instruction is received, judging the opening and closing functional state of the relay and the current of the two high-voltage ends of the relay according to the state parameters; and if the opening and closing functional state of the relay and the currents at the two high-voltage ends of the relay are normal, controlling the relay to be normally powered off, and recording after accumulating the times of normally powering off the relay for 1 time.
Specifically, when the vehicle is powered off or stops charging, the battery management system receives a relay disconnection instruction of the whole vehicle, and then starts to disconnect the relay. And the battery management system acquires state data before the relay is disconnected. The battery management system judges the functional state of the relay which is opened and closed according to the state data before the relay is opened, if the functional state is normal, the current of the high-voltage end of the relay is judged, if the functional state is normal, the relay can be powered off normally, the battery management system controls the relay to be opened, and the battery management system records the number of times that the relay is powered off normally for 1 time. The normal power-off times of the relay are counted by accumulating for 1 time every time.
Optionally, determining the power-on and power-off times of the relay according to the state parameter includes: when a relay closing instruction of the new energy automobile is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; if the relay is judged to be in a normal open and close functional state, the current at the two high-voltage ends of the relay is abnormal, and the relay is controlled to be closed and electrified if the relay is allowed to be closed, and the abnormal electrification times of the relay are accumulated for 1 time and then recorded.
Specifically, for example, when the vehicle is started or the vehicle is charged, the battery management system receives a relay closing instruction of the entire vehicle, and then starts to close the relay. And collecting state data before the relay is closed by the battery management system. The battery management system judges the functional state of the opening and closing of the relay according to the state data of the relay, if the functional state is normal, the current of the high-voltage end of the relay is judged, if the functional state is abnormal, the battery management system judges whether the relay is allowed to be closed or not, and if the relay is allowed to be closed, the battery management system controls the relay to be closed. The battery management system records the abnormal power-on times of the relay for 1 time. And accumulating 1 time for each abnormal power-on, thereby counting the abnormal power-on times. And if the battery management system judges that the current of the high-voltage end is abnormal and judges that the relay is not allowed to be closed, reporting the power-on failure of the whole vehicle.
Optionally, determining the power-on and power-off times of the relay according to the state parameter includes: when a new energy automobile relay opening instruction is received, judging the relay opening and closing function state and the current at the two high-voltage ends of the relay according to the state parameters; if the relay is judged to be in a normal open and close functional state, the currents at the two high-voltage ends of the relay are abnormal, but the relay is controlled to be opened and closed, the relay is controlled to be powered off, and the times of abnormal power off of the relay are accumulated for 1 time and then recorded.
Specifically, for example, when the vehicle is powered off or stops charging, the battery management system receives a relay opening instruction of the entire vehicle, and then starts to open the relay. And the battery management system acquires state data before the relay is disconnected. The battery management system judges the functional state of the relay which is opened and closed according to the state data before the relay is opened, if the functional state is normal, the current of the high-voltage end of the relay is judged, if the functional state is abnormal, the battery management system controls the relay to be opened, and the battery management system records the abnormal power-off times of the relay for 1 time. And accumulating for 1 time every time of abnormal power-off, thereby counting the abnormal power-off times of the relay.
Optionally, determining the number of times of the fault of the relay according to the state parameter includes:
when the battery management system receives a relay closing instruction of the new energy automobile, judging the state of the relay opening and closing function according to the state parameters; and if the open/close functional state fault of the relay is judged, accumulating the times of the power-on fault of the relay for 1 time and then recording.
Specifically, for example, when the vehicle is started or the vehicle is charged, the battery management system receives a relay closing instruction of the entire vehicle, and then starts to close the relay. And a battery management system acquires state data before the relay is closed. And the battery management system judges that the state of the relay is a fault according to the state data of the relay, the relay fault cannot be electrified, and the battery management system records the number of times of the electrified faults of the relay for 1 time. The fault of the relay is accumulated for 1 time each time. Thereby counting the failure times of the relay. And then the battery management system reports the faults of the relay of the whole vehicle.
Optionally, determining the number of times of the fault of the relay according to the state parameter includes: when a new energy automobile relay opening instruction is received, judging the relay opening and closing function state according to the state parameters; and if the relay is judged to have the fault of the open/close functional state, accumulating the times of the power-off fault of the relay for 1 time and then recording.
Specifically, when the vehicle is powered off or stops charging, the battery management system receives a relay disconnection instruction of the whole vehicle, and then starts to disconnect the relay. And the battery management system acquires state data before the relay is disconnected. And the battery management system judges that the state of the relay is a fault according to the state data before the relay is disconnected, the relay cannot be powered off when the relay is in fault, and the battery management system records the power-off fault frequency of the relay for 1 time. Each relay fault is accumulated for 1 time. Thereby counting the failure times of the relay. And then the battery management system reports the fault of the relay of the whole vehicle.
Fig. 4 is a schematic diagram of a power-on process of an on-line detection method for a new energy vehicle relay according to an embodiment of the present invention. Referring to fig. 4, the embodiment may be adapted to record the number of normal, abnormal power-on and failure times, and the method may be performed by a battery management system, and includes the steps of:
s001, starting or charging the vehicle, wherein the battery management system receives a relay closing instruction of the whole vehicle, and then starts to close the relay;
s002, collecting state data of the relay before closing by a data detection platform;
step S003, the battery management system judges whether the functional state data of the open and close of the relay is normal according to the state data of the relay, if the functional state of the open and close of the relay is normal, the step S004 is executed to judge the current at the two high-voltage ends of the relay; if the functional state data of the open and close of the relay is abnormal, executing the step S005 that the relay fails to be electrified; then step S006 the battery management system records the number of times of power failure on the relay for 1 time. Each relay fault is accumulated for 1 time. Thereby counting the failure times of the relay; finally, the battery management system reports the fault of the whole vehicle relay in the step S007;
step S004, the battery management system judges whether the current of the high-voltage end of the relay is normal, and if the current of the high-voltage end of the relay is normal, the step S008 is executed to close the relay; and finally, step S009 the battery management system records the normal power-on times of the relay for 1 time. Accumulating for 1 time every time the relay is normally electrified, so as to count the normal electrification times of the relay; if the current of the high-voltage end of the relay is abnormal, the step S010 needs to be executed to judge whether the relay is closed or not due to the abnormal current, and if the relay is not allowed to be closed, the step S011 is executed to report the failure of the whole vehicle power-on; if the closing is not allowed, executing step S012 to close the relay; and finally, executing the step S013, wherein the battery management system records the abnormal electrification times of the relay for 1 time. And accumulating for 1 time every time of abnormal power-on, thereby counting the abnormal power-on times of the relay.
Fig. 5 is a schematic power-off flow diagram of an on-line detection method for a new energy vehicle relay according to an embodiment of the invention. Referring to fig. 5, the present embodiment may be adapted to record normal, abnormal power down and number of failures, and the method may be performed by a battery management system, and the method comprises the steps of:
step S014, when the vehicle is powered off or stops charging, the battery management system receives a relay disconnection command of the whole vehicle, and the relay is disconnected at the moment;
step S015, collecting state data before the relay is disconnected by a data detection platform;
step S016, the battery management system judges whether the functional state of the relay which is opened and closed is normal according to the state data before the relay is opened; if the functional state of the opening and closing of the relay is normal, executing the step S020 to judge the current at the two high-voltage ends of the relay; if the functional state data of the open and close of the relay is abnormal, executing the step S017 that the relay fails to be electrified due to fault; then step S018 is a battery management system that records the number of times of power-off failure of the relay by 1. Each relay fault is accumulated for 1 time. Thereby counting the failure times of the relay; finally, the battery management system reports the fault of the whole vehicle relay in the step S019;
step S020, judging whether the current of the high-voltage end of the relay is normal by the battery management system, and executing step S021 to disconnect the relay if the current of the high-voltage end of the relay is normal; and finally, executing a step S022 to record the normal power-down times of the relay for 1 time by the battery management system. Accumulating the normal power-off times of the relay for 1 time every time, thereby counting the normal power-off times of the relay; if the current of the high-voltage end of the relay is abnormal, the step S023 is executed to disconnect the relay; and finally, executing a step S024 to record the abnormal power-off times of the relay for 1 time by the battery management system. And accumulating for 1 time every time of abnormal power-off, thereby counting the number of abnormal power-on times of the relay.
Fig. 6 is a schematic flow chart of another new energy vehicle relay online detection method provided in the embodiment of the present invention, referring to fig. 6, executed by a cloud analysis platform, and the method includes:
s410, receiving detection information sent by a battery management system;
the detection information comprises state parameters of the relay, the number of times of normal power on and power off of the relay, the number of times of abnormal power on and power off and the number of times of faults of the relay. The state parameters of the relay comprise at least one of high-voltage two-end current of the relay, low-voltage two-end current of the relay, working temperature of the relay, high-voltage two-end voltage of the relay, low-voltage two-end voltage of the relay, whether the relay breaks down and the on or off state of the relay;
s420, generating estimated data according to the detection information, and sending the estimated data to a battery management system; the estimated data comprises the estimated service life of the relay and the fault probability of the relay.
Specifically, the detection information is input into the failure model of the detection relay, so that the service life of the relay and the probability of the fault of the relay are estimated. The service life data comprises normal power-on and power-off service life data, abnormal power-on and power-off probability data and fault probability data of the relay.
According to the technical scheme provided by the embodiment of the invention, the state parameters of the relay, the power-on and power-off times and the failure times are detected, the estimated residual life of the relay and the failure probability of the relay are obtained by using the cloud analysis platform, the data parameter acquisition and analysis of the relay are realized, and the failure of the relay is early warned by using the analysis result, so that a user is guided to maintain or replace the relay, the relay failure occurrence condition in the using process of the user is reduced, and the use experience of the user is improved.
Optionally, generating the pre-estimation data according to the detection information, and sending the pre-estimation data to the battery management system includes:
and calling a stored relay failure model of the battery management system, and inputting detection information into the failure model so as to obtain estimated data.
Specifically, the relay failure model of the type may be stored in advance according to the type of the relay, and for example, the process of obtaining the estimated data is as follows: when the detection information is received, a relay failure model which is stored in advance is called, the detection information is input into the failure model for calculation, and estimated data comprising the residual service life and the fault probability are output.
Fig. 7 is a schematic structural diagram of a battery management system according to an embodiment of the present invention, and referring to fig. 7, a battery management system 220 includes a data detection unit 230;
the data detection unit 230 is configured to detect a state parameter of the relay, determine the number of times of power-on and power-off of the relay and the number of times of faults according to the state parameter, and generate detection information;
the data detection unit 230 is further configured to send the detection information to the cloud analysis platform 120, and receive the estimated data sent by the cloud analysis platform 120; the detection information is used for the cloud analysis platform 120 to analyze according to the detection information to obtain pre-estimated data; the estimated data comprises the estimated service life of the relay and the fault probability of the relay.
Specifically, the state parameters of the relay include at least one of current at two high-voltage ends of the relay, current at two low-voltage ends of the relay, working temperature of the relay, voltage at two high-voltage ends of the relay, voltage at two low-voltage ends of the relay, whether the relay is in fault or not and on or off state of the relay; and judging whether the state of the relay is normal, abnormal or fault according to the state parameters of the relay, thereby determining and recording the times of normal power on and off, the times of abnormal power on and off and the times of fault of the relay and generating detection information.
The cloud analysis platform 120 and the data detection unit 230 may be connected through the data transmission unit 210; the data transmission unit 210 is configured to transmit the state parameters, the power-on and power-off times, and the failure times to the cloud analysis platform 120; the detection information may be sent to the cloud analysis platform 120 through wireless or wired communication. The cloud analysis platform 120 sends the estimated data to the battery management system 220 according to the detection information of the data detection unit 230, and the battery management system 220 reminds the user of maintaining or replacing the relay according to the estimated data. Illustratively, the process of acquiring the pre-estimated data by the cloud analysis platform 120 is as follows: when the receiving unit 121 receives the detection information, the pre-estimating unit 122 calls a relay failure model stored in advance, the pre-estimating unit 122 inputs the detection information into the failure model, and if fault data of the detection information reaches a fault threshold value in the relay failure model, the cloud analysis platform 120 outputs pre-estimated data including corresponding service life and fault probability; if the abnormal data of the detection information reaches the abnormal threshold value in the relay failure model, the cloud analysis platform 120 outputs estimated data including the corresponding service life and the abnormal fault probability.
With continued reference to fig. 7, the battery management system further includes a data storage unit 240;
the data storage unit 240 is connected to the data detection unit 230, and the data storage unit 240 is used for storing the detection information and the prediction data.
Specifically, the detection information includes a state parameter, the number of power-on and power-off times, and the number of faults. The estimated data comprises estimated service life of the relay and failure probability of the relay. The data storage unit 240 may store local data and cloud data, the local data including relay state parameters, the number of power on/off times, and the number of faults; the cloud data includes the data uploaded by the data detection unit 230 and the pre-estimation data sent by the cloud analysis platform 120. The data storage unit 230 is used for storing and backing up relay data, so that the relay data can be analyzed after being called, and the data utilization rate is improved.
The cloud analysis platform 120 may further include a storage unit 123; the storage unit 123 is connected with the estimation unit 122; the storage unit 123 is used for storing a relay failure model of the battery management system; the estimation unit 122 is further configured to invoke a stored failure model of the battery management system relay, and input detection information to the failure model, so as to obtain estimation data.
Fig. 8 is a schematic structural diagram of another battery management system according to an embodiment of the present invention. Referring to fig. 8, optionally, the data detection unit 230 further includes a current collection module 420, a temperature collection module 430, a voltage collection module 440, and a relay detection module 450; the current collecting module 420 is used for collecting the current at the high-voltage ends of the relay 460 and the current at the low-voltage ends of the relay 460; the temperature acquisition module 430 is used for acquiring the working temperature of the relay 460; the voltage acquisition module 440 is used for acquiring the voltage at the two high-voltage ends of the relay 460 and the voltage at the two low-voltage ends of the relay 460; the relay detection module 450 is used to detect the functional status of the relay 460 and the closed or open status of the relay 460.
Specifically, the current collecting module 420 collects the power-on and power-off process current of the relay 460 through the shunt 470, and can also control the low-voltage current of the relay 460; the temperature acquisition module 430 acquires the working temperature of the relay 460; the voltage acquisition module 440 acquires the voltage at the two high-voltage ends of the relay 460 and the voltage at the two low-voltage ends of the relay 460, and can also control the voltage of the working circuit of the relay 460; the relay detection module 450 detects whether the relay 460 has failed and detects a closed or open state of the relay 460. Generally, the battery management system 310 includes a current collection module 420, a temperature collection module 430, a voltage collection module 440, and a relay detection module 450, and the current device modules of the current new energy vehicle battery management system 310 can be utilized, and the state parameter detection collection and the control adjustment of the relay can be completed without adding other devices. In addition, the current collection module 420, the temperature collection module 430, the voltage collection module 440 and the relay detection module 450 can also be flexibly distributed and placed for independent modules according to engineering needs.
The embodiment of the invention also provides a battery pack which comprises the battery management system in any one of the embodiments of the invention.
Specifically, fig. 9 is a schematic structural diagram of an online detection system for a new energy vehicle relay according to an embodiment of the present invention. Referring to fig. 9, battery pack 360 includes main positive relay 320, main negative relay 330, battery management system 220, and battery 340. The battery management system 220 may directly transmit the state parameters of the main positive relay 320 and the main negative relay 330, and the data of the voltage and the current, the power-on and power-off times and the number of faults of the battery 340 to the cloud analysis platform 120 by itself, or may transmit the data to the cloud analysis platform 120 after being relayed through a gateway or an on-board internet TBOX 350. The cloud analysis platform 120 analyzes and predicts the detection information to generate predicted data, and reminds a user to maintain or replace the relay through the battery management system 220. The data transmission unit can also improve the data transmission distance and the data transmission rate, and simultaneously improve the data transmission quantity.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. The new energy automobile relay online detection method is characterized by being executed by a battery management system, and comprises the following steps:
detecting state parameters of the relay;
determining the times of power on and power off and the times of faults of the relay according to the state parameters, and generating detection information;
sending the detection information to a cloud analysis platform; the detection information is used for the cloud analysis platform to analyze according to the detection information to obtain pre-estimated data;
and receiving pre-estimated data sent by the cloud analysis platform, wherein the pre-estimated data comprises the pre-estimated service life of the relay and the fault probability of the relay.
2. The new energy automobile relay on-line detection method according to claim 1,
determining the number of times of powering on and powering off the relay according to the state parameter comprises:
when a relay closing instruction of the new energy automobile is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; and if the opening and closing functional state of the relay and the currents at the two high-voltage ends of the relay are normal, controlling the relay to be closed and normally electrified, and recording after accumulating the times of normally electrified relay for 1 time.
3. The new energy automobile relay on-line detection method according to claim 1,
determining the number of times of powering on and powering off the relay according to the state parameter comprises:
when the new energy automobile relay opening instruction is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; and if the relay opening and closing function state and the currents at the two high-voltage ends of the relay are normal, controlling the relay to be normally powered off, and recording after accumulating the times of normally powering off the relay for 1 time.
4. The new energy automobile relay on-line detection method according to claim 1,
determining the number of times of powering on and powering off the relay according to the state parameter comprises:
when a relay closing instruction of the new energy automobile is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; and if the state of the relay opening and closing function is judged to be normal, the current at the two high-voltage ends of the relay is abnormal, and the relay is controlled to be closed and electrified if the relay is allowed to be closed, and the times of abnormal electrification of the relay are accumulated for 1 time and then recorded.
5. The new energy automobile relay on-line detection method according to claim 1,
determining the number of times of powering on and powering off the relay according to the state parameter comprises:
when the new energy automobile relay opening instruction is received, judging the relay opening and closing function state and the current of the two high-voltage ends of the relay according to the state parameters; and if the relay is judged to be in a normal open and close functional state, the current at the two high-voltage ends of the relay is abnormal, but the relay is controlled to be opened and closed, and the abnormal power-off times of the relay are accumulated for 1 time and then recorded.
6. The new energy automobile relay on-line detection method according to claim 1,
determining the number of failures of the relay according to the state parameter comprises:
when the battery management system receives a relay closing instruction of the new energy automobile, judging the state of the relay opening and closing function according to the state parameters; and if the open/close functional state fault of the relay is judged, accumulating the times of the power-on fault of the relay for 1 time and then recording.
7. The new energy automobile relay on-line detection method according to claim 1,
determining the number of failures of the relay according to the state parameter comprises:
when the new energy automobile relay opening instruction is received, judging the relay opening and closing function state according to the state parameters; and if the open/close functional state fault of the relay is judged, accumulating the times of the power-off fault of the relay for 1 time and then recording.
8. A battery management system, comprising a data detection unit;
the data detection unit is used for detecting state parameters of the relay, determining the times of power-on and power-off of the relay and the times of faults according to the state parameters, and generating detection information;
the data detection unit is further used for sending the detection information to a cloud analysis platform and receiving pre-estimated data sent by the cloud analysis platform; the detection information is used for the cloud analysis platform to analyze according to the detection information to obtain pre-estimated data; the estimated data comprises the estimated service life of the relay and the fault probability of the relay.
9. The battery management system of claim 8, further comprising a data storage unit;
the data storage unit is connected with the data detection unit and is used for storing the detection information and the pre-estimated data.
10. A battery pack comprising the battery management system of any one of claims 8 to 9.
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