CN117549883A - Safety supervision system for battery pack of hybrid electric vehicle - Google Patents
Safety supervision system for battery pack of hybrid electric vehicle Download PDFInfo
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Abstract
The invention relates to a battery pack safety supervision system of a hybrid electric vehicle, in particular to the technical field of battery pack safety supervision, which comprises the following components: the system comprises an information acquisition module, a state monitoring module, a state analysis module, an aging degree analysis module, a correction module, a charging depth management module, a management module and an optimization module, wherein the information acquisition module acquires battery pack information, vehicle information, road condition information and environment information, the state monitoring module analyzes the state of the battery pack, and performs abnormal early warning according to analysis results, the state analysis module analyzes abnormal state time of the battery pack, adjusts the analysis process of the abnormal state time of the state of the battery pack, the aging degree analysis module analyzes the aging degree of the battery pack, the correction module corrects the analysis process of the aging degree of the battery pack, the charging depth management module manages the lowest charging depth of the battery pack in the next monitoring period, and the optimization module optimizes the analysis process of the abnormal state of the battery pack in the next management period.
Description
Technical Field
The invention relates to the technical field of battery pack safety supervision, in particular to a battery pack safety supervision system of a hybrid electric vehicle.
Background
With the popularization and application of hybrid vehicles, the safety of the battery pack has become an important issue. Because the battery pack may generate problems of overheat, overcharge, overdischarge and the like in the charge and discharge process, if the battery pack is not monitored and processed in time, serious consequences such as damage, fire disaster and the like of the battery pack may be caused, and the service life of the battery is seriously influenced, especially in high-temperature and high-altitude areas, the service life of the battery is influenced more, so that the development of a reliable battery pack safety supervision system becomes a problem to be solved urgently.
Chinese patent publication No.: CN103332190B discloses a control device and a control method for fuel oil power generation of an electric hybrid car: the control device comprises a signal processing module, a main control module and an output control module, wherein the signal processing module is connected with a signal pickup source of the engine fuel power generation system, the signal processing module is connected with the main control module, and the main control module is connected with the power generation system execution hardware through the output control module. The signal processing module picks up part or all of the working condition signals to be processed, and then judges and compares the working condition signals through the main control module, and then sends an instruction to the output control module, and the output control module controls the fuel power generation execution hardware to work according to the instruction sent by the main control module. The whole process is automatically controlled, and the phenomenon of power battery pack power shortage or overcharge is avoided; therefore, in the analysis process of the fuel oil power generation control of the electric hybrid automobile, the scheme only considers voltage and current, and can not effectively manage the battery pack in a high-temperature and high-altitude area, so that the problems of low management efficiency of the battery pack and low service life of the battery pack exist.
Disclosure of Invention
Therefore, the invention provides a battery pack safety supervision system of a hybrid electric vehicle, which is used for solving the problems of low management efficiency and low service life of the battery pack in the prior art.
In order to achieve the above object, the present invention provides a hybrid electric vehicle battery pack safety supervision system, the system comprising,
the information acquisition module is used for acquiring battery pack information, vehicle information, road condition information and environment information;
the state monitoring module is used for analyzing the state of the battery pack according to the acquired battery pack voltage, battery pack current and battery pack temperature and carrying out abnormal early warning according to an analysis result;
the state analysis module is used for acquiring voltage early warning time, current early warning time and temperature early warning time in the monitoring period, analyzing the state abnormal time of the battery pack according to the voltage early warning time, the current early warning time and the temperature early warning time in the monitoring period, and adjusting the analysis process of the state abnormal time of the battery pack according to the length of a climbing road section in the monitoring period;
the aging degree analysis module is used for analyzing the aging degree of the battery pack according to the acquired internal resistance and capacity of the battery pack;
The correction module is used for correcting the analysis process of the aging degree of the battery pack according to the acquired environmental temperature and the altitude of the management period, is provided with a correction unit used for correcting the analysis process of the aging degree of the battery pack according to the acquired environmental temperature of the management period, and is also provided with a compensation unit used for compensating the correction process of the analysis process of the aging degree of the battery pack according to the acquired altitude;
the charging depth management module is used for managing the lowest charging depth of the battery pack in the next monitoring period according to the analysis result of the state abnormal time of the battery pack in the monitoring period and the analysis result of the aging degree of the battery pack;
and the optimization module is used for optimizing the adjustment process of the analysis process of the abnormal state of the battery pack in the next management period according to the aging rate of the battery pack in the current management period.
Further, the state monitoring module is provided with a voltage analysis unit, the voltage analysis unit compares the obtained battery voltage a0 with each preset voltage, and analyzes the voltage state of the battery according to the comparison result, wherein:
when a0 is less than or equal to a1 or a0 is more than or equal to a2, the voltage analysis unit judges that the voltage of the battery pack is abnormal and performs voltage early warning;
When a1 is more than a0 and less than a2, the voltage analysis unit judges that the voltage of the battery pack is normal and does not perform early warning; wherein a1 is a preset minimum voltage, and a2 is a preset maximum voltage;
the state monitoring module is also provided with a current analysis unit, the current analysis unit compares the acquired battery current b0 with each preset current and analyzes the current state of the battery according to the comparison result, wherein:
when b0 is less than or equal to b1 or b0 is more than or equal to b2, the current analysis unit judges that the current of the battery pack is abnormal and performs current abnormality early warning;
when b1 is more than b0 and less than b2, the current analysis unit judges that the current of the battery pack is normal, and early warning is not carried out; wherein b1 is a preset minimum current, and b2 is a preset maximum current;
the state monitoring module is also provided with a temperature analysis unit, the temperature analysis unit compares the acquired battery pack temperature c0 with each preset temperature and analyzes the temperature state of the battery pack according to the comparison result, wherein:
when c0 is less than or equal to c1 or c0 is more than or equal to c2, the temperature analysis unit judges that the temperature of the battery pack is abnormal and performs temperature abnormality early warning;
when c1 is more than c0 and less than c2, the temperature analysis unit judges that the temperature of the battery pack is normal, and early warning is not carried out; wherein c1 is the minimum preset temperature, and c2 is the maximum preset temperature.
Further, the state analysis module is provided with a state analysis unit, the state analysis unit respectively compares the voltage early-warning time D1, the current early-warning time D2 and the temperature early-warning time D3 in the monitoring period with a preset abnormal time D0, and analyzes the state abnormal time of the battery pack according to the comparison result, wherein:
when D1 is less than or equal to D0, the state analysis unit judges that the abnormal time of the battery pack voltage in the monitoring period is normal, and when D1 is more than D0, the state analysis unit judges that the abnormal time of the battery pack voltage in the monitoring period is long, and outputs the abnormal time of the battery pack voltage to a user;
when D2 is less than or equal to D0, the state analysis unit judges that the abnormal time of the battery current in the monitoring period is normal, and when D2 is more than D0, the state analysis unit judges that the abnormal time of the battery current in the monitoring period is long and outputs the abnormal time of the battery current to a user;
when D3 is less than or equal to D0, the state analysis unit judges that the temperature abnormality time of the battery pack in the monitoring period is normal, and when D3 is more than D0, the state analysis unit judges that the temperature abnormality time of the battery pack in the monitoring period is long, and outputs the temperature abnormality time of the battery pack to a user.
Further, the state analysis module is further provided with an adjusting unit, the adjusting unit compares the length f0 of the climbing road section in the monitoring period with the preset length f1, and adjusts the analysis process of the abnormal state of the battery pack according to the comparison result, wherein:
when f0 is less than or equal to f1, the adjusting unit judges that the length of the climbing road section is normal, and no adjustment is performed;
when f0 > f1, the adjusting unit judges that the length of the climbing road section is abnormal, sets an adjusting coefficient alpha to adjust the analysis process of the abnormal state of the battery pack, and sets alpha=e 3(f0-f1)/f0-3 The adjusted preset abnormal time is set to D0', and D0' =d0×α is set.
Further, the aging degree analysis module is provided with a parameter analysis unit, and the parameter analysis unit analyzes the acquired internal resistance n1, the battery capacity m1, the initial internal resistance n0 and the initial capacity m0 of the battery to the parameters of the battery, wherein:
when (n 0-n 1)/n 0 is less than or equal to e1, the parameter analysis unit judges that the internal resistance of the battery pack is normal;
when (n 0-n 1)/n 0 > e1, the parameter analysis unit determines that the internal resistance of the battery pack is abnormal;
when (m 0-m 1)/m 0 is less than or equal to e2, the parameter analysis unit judges that the capacity of the battery pack is normal; when (m 0-m 1)/m 0 > e2, the parameter analysis unit determines that the battery pack capacity is abnormal.
Further, the aging degree analysis module is further provided with an aging degree analysis unit, and the aging degree analysis unit analyzes the aging degree of the battery pack according to the analysis result of the battery pack parameter, wherein:
when the internal resistance of the battery pack is normal and the capacity of the battery pack is normal, the aging degree analysis unit sets the aging degree of the battery pack to L1, and sets l1=0;
when the internal resistance of the battery is abnormal and the capacity of the battery is normal, the aging degree analysis unit sets the aging degree of the battery to L2, and sets l2=0.6xsin [ (n 0-n 1)/n 0 x (pi/2) ];
when the internal resistance of the battery is normal and the capacity of the battery is abnormal, the aging degree analysis unit sets the aging degree of the battery to L3, and sets l3=0.4× [ (n 0-n 1)/n 0-e1 ]/(n 0-n 1)/n 0;
when the internal resistance of the battery is abnormal and the capacity of the battery is abnormal, the aging degree analysis unit sets the aging degree of the battery to L4, and sets l4=0.6xsin [ (n 0-n 1)/n0× (pi/2) ]+0.4× [ (n 0-n 1)/n 0-e1 ]/(n 0-n 1)/n 0.
Further, the correction unit will manage the ambient temperature t0 in the cycle i Comparing the aging degree of the battery pack with each preset temperature, and correcting the aging degree of the battery pack according to the comparison result, wherein:
when t0 i T1 or t0 is less than or equal to i When the temperature is not less than t2, the correction unit judges that the ambient temperature is abnormal;
when t1 < t0 i When the temperature is less than t2, the correction unit judges that the ambient temperature is normal;
the correction unit sets the number of abnormal ambient temperature times in the management period as r, sets a correction coefficient Y to correct the analysis process of the aging degree of the battery pack, and sets Y=1+2/pi×arctan [ r/2T×pi ]]The aging degree L of the battery pack after correction R Let L be R ' set L R ’=L R ×Y，R=1,2,3,4，t0 i For the ambient temperature of the ith day in the management period, i is more than 0 and less than or equal to T, T is the number of days in the management period, T1 is the preset minimum temperature, and T2 is the preset maximum temperature.
Further, the compensation unit compares the obtained altitude h0 with a preset altitude h1, and compensates a correction process of the battery pack aging degree analysis process according to the comparison result, wherein:
when h0 is less than or equal to h1, the compensation unit judges that the altitude is normal and does not compensate;
when h0 > h1, the compensation unit determines that the altitude is abnormal, and sets a compensation coefficient Z to compensate for the correction process of the battery pack aging analysis process, and z=1+ (h0-h 1)/(h0+h1).
Further, the charging depth management module manages the lowest charging depth of the battery pack in the next monitoring period according to the analysis result of the abnormal time of the battery pack in the monitoring period and the aging degree of the battery pack, wherein:
When the battery voltage abnormality time is normal and the battery current abnormality time is normal and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q1, and sets Q1=q0× {1+w1×sin [ L ] R ×(π/2)]};
When the battery voltage abnormality time is long and the battery current abnormality time is normal and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q2, and sets Q2=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is long and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q3, and sets Q3=q0× {1+w1×sin [ L ] R ×(π/2)]+w3×(d2-d0)/(d2+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is normal and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q4, and sets Q4=q0× {1+w1×sin [ L ] R ×(π/2)]+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is long and the battery temperature abnormality time is normal, the charging depth management module monitors the battery in the next monitoring period The lowest charge depth of the group is set to Q5, and q4=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w3×(d2-d0)/(d2+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is normal and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q6, and sets Q6=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is long and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q7, and sets Q7=q0× {1+w1×sin [ L ] R ×(π/2)]+w3×(d2-d0)/(d2+d0)+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is long and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q8, and sets Q8=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w3×(d2-d0)/(d2+d0)+w4×(d3-d0)/(d3+d0)};
The charging depth management module analyzes the analysis result Q of the lowest charging depth u Outputting to a user;
wherein u=1, 2..8, w1 is the age weight, w2 is the voltage anomaly weight, w3 is the current anomaly weight, w4 is the temperature anomaly weight, w1+w2+w3+w4=1, w1 > w3 > w2 > w4.
Further, the optimization module compares the aging rate v0 of the battery pack in the current management period with the preset aging rate v1, and optimizes the adjustment process of the state anomaly time analysis process of the battery pack in the next management period according to the comparison result, wherein:
When v0 is less than or equal to v1, the optimization module judges that the aging rate of the battery pack is slow and does not perform optimization;
when v0 > v1, the optimizing module determines that the aging rate of the battery pack is fast, sets an optimizing coefficient beta to optimize the adjusting process of the analysis process of the state anomaly time of the battery pack in the next management period, sets beta=1- (v 0-v 1)/(v0+v1), sets the optimized adjusting coefficient to alpha ', and sets alpha' =alpha×beta.
Compared with the prior art, the invention has the advantages that the voltage analysis unit improves the accuracy of the voltage abnormality pre-warning by setting the preset voltage so as to improve the accuracy of the analysis of the abnormal time of the state of the battery, thereby improving the management efficiency of the battery pack, and finally improving the service life of the battery pack, the current analysis unit improves the accuracy of the current abnormality pre-warning by setting the preset current so as to improve the accuracy of the analysis of the abnormal time of the state of the battery, thereby improving the management efficiency of the battery pack, and finally improving the service life of the battery pack, the temperature analysis unit improves the accuracy of the analysis of the abnormal time of the state of the battery by setting the preset temperature so as to improve the management efficiency of the abnormal time of the state of the battery pack, and finally improving the management efficiency of the battery pack, and prolonging the service life of the battery pack by setting the preset abnormal time so as to improve the accuracy of the state abnormality analysis of the battery pack, and finally improving the management efficiency of the battery pack by setting the preset abnormal time, the aging factor of the battery pack, and finally improving the quality of the battery pack by setting the preset abnormal time of the state of the battery, the battery pack management efficiency is finally improved, the battery pack service life is prolonged, the correction unit is used for improving the accuracy of correction coefficient through setting preset temperature, and further improving the accuracy of battery pack aging analysis, so that the management efficiency of the battery pack charging depth is improved, the battery pack management efficiency is finally improved, and the battery pack service life is prolonged, the compensation unit is used for improving the accuracy of compensation coefficient through setting preset elevation, further improving the accuracy of battery pack aging analysis, so that the management efficiency of the battery pack charging depth is improved, the management efficiency of the battery pack is finally improved, the battery pack service life is prolonged, the battery pack minimum charging depth analysis accuracy is improved through setting aging degree weight, voltage abnormal weight, current abnormal weight and temperature abnormal weight, so that the management efficiency of the battery pack charging depth is improved, the battery pack management efficiency is finally improved, the battery pack service life is prolonged, and the battery pack state abnormal time analysis accuracy is improved through setting preset aging rate so that the accuracy of the optimization coefficient is improved, the battery pack charging depth management efficiency is improved, and the battery pack service life is finally prolonged.
Drawings
Fig. 1 is a schematic structural diagram of a battery pack safety supervision system of a hybrid vehicle according to the present embodiment;
FIG. 2 is a schematic diagram of a status monitoring module according to the present embodiment;
FIG. 3 is a schematic diagram of a state analysis module according to the present embodiment;
FIG. 4 is a schematic diagram of the aging analysis module according to the present embodiment;
fig. 5 is a schematic structural diagram of the calibration module according to the present embodiment.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, a schematic structural diagram of a battery pack safety supervision system for a hybrid electric vehicle according to the present embodiment is shown, which includes,
the information acquisition module is used for acquiring battery pack information, vehicle information, road condition information and environment information, wherein the battery pack information comprises battery pack voltage, battery pack current and battery pack temperature, the vehicle information comprises battery pack capacity, battery pack internal resistance, battery pack initial internal resistance and battery pack initial capacity, the road condition information is climbing road section length, and the environment information comprises environment temperature and altitude; in this embodiment, the method for acquiring the battery pack information, the vehicle information, the road condition information and the environmental information is not specifically limited, and can be freely set by a person skilled in the art, and only the acquisition requirements of the battery pack information, the vehicle information, the road condition information and the environmental information are met, wherein the battery pack information can be acquired through a vehicle-mounted diagnosis tool, the battery pack capacity can be acquired through a charge-discharge test, the battery pack internal resistance can be calculated by detecting a group of output currents and voltages of the battery before and after the starting of the automobile through a whole automobile controller, the initial internal resistance of the battery pack and the initial capacity of the battery pack can be acquired through interaction, the altitude can be acquired through a GPS positioning system, the road condition information can be acquired through third-party map software, and the environmental temperature can be acquired through a weather website;
The state monitoring module is used for analyzing the state of the battery pack according to the acquired battery pack voltage, battery pack current and battery pack temperature and carrying out abnormal early warning according to an analysis result, and is connected with the information acquisition module;
the state analysis module is used for acquiring voltage early warning time, current early warning time and temperature early warning time in the monitoring period, analyzing the state abnormal time of the battery pack according to the voltage early warning time, the current early warning time and the temperature early warning time in the monitoring period, adjusting the analysis process of the state abnormal time of the battery pack according to the length of a climbing road section in the monitoring period, and connecting with the state monitoring module; in this embodiment, the setting of the monitoring period is not specifically limited, and a person skilled in the art can freely set the monitoring period only by meeting the setting requirement of the monitoring period, wherein the monitoring period can be set to be 5 days, 7 days, 10 days, etc.;
the aging degree analysis module is used for analyzing the aging degree of the battery pack according to the acquired internal resistance and capacity of the battery pack, and is connected with the state analysis unit;
The correction module is used for correcting the aging degree analysis process of the battery pack according to the acquired environmental temperature and altitude of the management period, and is connected with the aging degree analysis module; in this embodiment, the management period time is longer than the monitoring period, and the setting of the management period is not specifically limited, so that a person skilled in the art can freely set the management period time only by meeting the setting requirement of the management period, wherein the management period can be set to 20 days, 30 days, 50 days, and the like;
the charging depth management module is used for managing the lowest charging depth of the battery pack in the next monitoring period according to the analysis result of the state abnormal time of the battery pack in the monitoring period and the analysis result of the aging degree of the battery pack, and is connected with the correction module;
the optimizing module is used for optimizing the adjusting process of the analysis process of the abnormal state of the battery pack in the next management period according to the aging rate of the battery pack in the current management period, and is connected with the charging depth management module; in this embodiment, the calculation mode of the aging rate of the battery pack is not specifically limited, and a person skilled in the art can freely set the calculation mode only by meeting the aging rate calculation requirement, wherein the calculation formula of the aging rate can be set as v0= (L) R -L R0 )/T，L R Battery pack aging degree, L, for current management period R0 Managing periods for adjacent historiesThe aging degree of the battery pack, T, is the number of days of the management cycle.
Fig. 2 is a schematic structural diagram of a status monitoring module according to the present embodiment, where the status monitoring module includes,
the voltage analysis unit is used for analyzing the voltage state of the battery pack according to the acquired voltage of the battery pack and carrying out voltage abnormality early warning according to an analysis result;
the current analysis unit is used for analyzing the current state of the battery pack according to the acquired current of the battery pack and carrying out current abnormality early warning according to an analysis result, and is connected with the voltage analysis unit;
and the temperature analysis unit is used for analyzing the temperature state of the battery pack according to the acquired temperature of the battery pack and carrying out temperature abnormality early warning according to an analysis result, and is connected with the current analysis unit.
Fig. 3 is a schematic structural diagram of a state analysis module according to the present embodiment, where the state analysis module includes,
the acquisition unit is used for acquiring voltage early warning time, current early warning time and temperature early warning time in the monitoring period;
the state analysis unit is used for analyzing the abnormal state time of the battery pack according to the voltage early-warning time, the current early-warning time and the temperature early-warning time in the monitoring period, and is connected with the acquisition unit;
And the adjusting unit is used for adjusting the analysis process of the state abnormal time of the battery pack according to the length of the climbing road section in the monitoring period, and is connected with the state analysis unit.
Fig. 4 is a schematic structural diagram of an aging degree analysis module according to the present embodiment, where the aging degree analysis module includes,
a parameter analysis unit for analyzing parameters of the battery pack according to the obtained internal resistance, the battery pack capacity, the initial internal resistance and the initial capacity of the battery pack;
and the aging degree analysis unit is used for analyzing the aging degree of the battery pack according to the analysis result of the battery pack parameters, and is connected with the parameter analysis unit.
Referring to fig. 5, a schematic structural diagram of a calibration module according to the present embodiment is shown, where the calibration module includes,
the correction unit is used for correcting the analysis process of the aging degree of the battery pack according to the acquired environmental temperature of the management period;
and the compensation unit is used for compensating the correction process of the analysis process of the aging degree of the battery pack according to the acquired altitude, and is connected with the correction unit.
Specifically, the embodiment is applied to the safety supervision of the battery pack of the hybrid electric vehicle in the high-temperature high-altitude area, and the minimum charging depth of the battery pack is managed according to the analysis result of the battery pack state abnormal time and the analysis result of the battery pack aging degree by analyzing the voltage, the current and the temperature of the battery pack and analyzing the battery pack state abnormal time.
Specifically, the voltage analysis unit increases the accuracy of the voltage abnormality pre-warning by setting a preset voltage, thereby increasing the accuracy of the analysis of the state abnormality time of the battery pack, thereby increasing the management efficiency of the depth of charge of the battery pack, and eventually increases the life of the battery pack, the current analysis unit increases the accuracy of the current abnormality pre-warning by setting a preset current, thereby increasing the accuracy of the analysis of the state abnormality time of the battery pack, thereby increasing the management efficiency of the depth of charge of the battery pack, and eventually increases the management efficiency of the battery pack, and increases the life of the battery pack, the temperature analysis unit increases the management efficiency of the depth of charge of the battery pack by setting a preset temperature, thereby increasing the accuracy of the analysis of the state abnormality time of the battery pack, thereby increasing the management efficiency of the state abnormality time of the battery pack, eventually increases the management efficiency of the battery pack, and eventually increases the life of the battery pack, the state analysis unit increases the life of the battery pack by setting a preset current to increase the accuracy of the state abnormality time of the current abnormality pre-warning, and eventually increases the management efficiency of the battery pack, and thereby increasing the life of the battery pack by setting a preset current to increase the accuracy of the state abnormality time of the state abnormality pre-warning, and finally increases the management efficiency of the battery pack, and thereby increasing the accuracy of the state abnormality time of charge of the battery pack, and thereby increases the quality of the battery pack by setting a temperature of the quality of the battery pack, the battery pack life is prolonged, the correction unit is used for improving the accuracy of correction coefficients by setting preset temperatures, further improving the accuracy of analysis of the aging degree of the battery pack, thereby improving the management efficiency of the battery pack, finally improving the management efficiency of the battery pack, and prolonging the battery pack life, the compensation unit is used for improving the accuracy of compensation coefficients by setting preset altitudes, further improving the accuracy of analysis of the aging degree of the battery pack, thereby improving the management efficiency of the battery pack charging depth, finally improving the management efficiency of the battery pack, and prolonging the battery pack life, and the charging depth management module is used for improving the accuracy of analysis of the lowest charging depth of the battery pack by setting aging degree weights, voltage abnormal weights, current abnormal weights and temperature abnormal weights, thereby improving the management efficiency of the battery pack, finally improving the management efficiency of the battery pack, prolonging the battery pack life, and the optimization module is used for improving the management efficiency of the battery pack charging depth by setting preset aging rates, further improving the accuracy of analysis of the state abnormal time of the battery pack, and finally improving the management efficiency of the battery pack charging depth, and prolonging the battery pack life.
Specifically, the voltage analysis unit compares the obtained battery voltage a0 with each preset voltage, and analyzes the voltage state of the battery according to the comparison result, wherein:
when a0 is less than or equal to a1 or a0 is more than or equal to a2, the voltage analysis unit judges that the voltage of the battery pack is abnormal and performs voltage early warning;
when a1 is more than a0 and less than a2, the voltage analysis unit judges that the voltage of the battery pack is normal and does not perform early warning; wherein a1 is a preset minimum voltage, and a2 is a preset maximum voltage.
Specifically, the voltage analysis unit improves the accuracy of early warning of abnormal voltage by setting preset voltage, and further improves the accuracy of analysis of abnormal state time of the battery pack, so that the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset voltage is not specifically limited, and a person skilled in the art can freely set the preset voltage only by meeting the value requirement of the preset voltage, wherein the optimal value of a1 is 200 volts, and the optimal value of a2 is 380 volts.
Specifically, the current analysis unit compares the obtained battery current b0 with each preset current, and analyzes the current state of the battery according to the comparison result, wherein:
When b0 is less than or equal to b1 or b0 is more than or equal to b2, the current analysis unit judges that the current of the battery pack is abnormal and performs current abnormality early warning;
when b1 is more than b0 and less than b2, the current analysis unit judges that the current of the battery pack is normal, and early warning is not carried out; wherein b1 is a preset minimum current, and b2 is a preset maximum current.
Specifically, the current analysis unit improves the accuracy of current abnormality early warning by setting preset current, and further improves the accuracy of battery state abnormality time analysis, so that the management efficiency of the battery charging depth is improved, the management efficiency of the battery is finally improved, and the service life of the battery is prolonged; in this embodiment, the setting of the preset current is not specifically limited, and a person skilled in the art can freely set the preset current only by meeting the value requirement of the preset current, wherein the optimal value of b1 is 50 a, and the optimal value of a2 is 120 a.
Specifically, the temperature analysis unit compares the obtained battery pack temperature c0 with each preset temperature, and analyzes the temperature state of the battery pack according to the comparison result, wherein:
when c0 is less than or equal to c1 or c0 is more than or equal to c2, the temperature analysis unit judges that the temperature of the battery pack is abnormal and performs temperature abnormality early warning;
When c1 is more than c0 and less than c2, the temperature analysis unit judges that the temperature of the battery pack is normal, and early warning is not carried out; wherein c1 is the minimum preset temperature, and c2 is the maximum preset temperature.
Specifically, the temperature analysis unit improves the accuracy of early warning of temperature abnormality by setting preset temperature, and further improves the accuracy of analysis of abnormal time of the state of the battery pack, so that the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset temperature is not specifically limited, and a person skilled in the art can freely set the preset temperature only by meeting the value requirement of the preset temperature, wherein the optimal value of c1 is-15 ℃, and the optimal value of c2 is 60 ℃.
Specifically, the state analysis unit compares the voltage early-warning time D1, the current early-warning time D2 and the temperature early-warning time D3 in the monitoring period with a preset abnormal time D0 respectively, and analyzes the state abnormal time of the battery pack according to a comparison result, wherein:
when D1 is less than or equal to D0, the state analysis unit judges that the abnormal time of the battery pack voltage in the monitoring period is normal, and when D1 is more than D0, the state analysis unit judges that the abnormal time of the battery pack voltage in the monitoring period is long, and outputs the abnormal time of the battery pack voltage to a user;
When D2 is less than or equal to D0, the state analysis unit judges that the abnormal time of the battery current in the monitoring period is normal, and when D2 is more than D0, the state analysis unit judges that the abnormal time of the battery current in the monitoring period is long and outputs the abnormal time of the battery current to a user;
when D3 is less than or equal to D0, the state analysis unit judges that the temperature abnormality time of the battery pack in the monitoring period is normal, and when D3 is more than D0, the state analysis unit judges that the temperature abnormality time of the battery pack in the monitoring period is long, and outputs the temperature abnormality time of the battery pack to a user.
Specifically, the state analysis unit improves the accuracy of state abnormal time analysis of the battery pack by setting preset abnormal time, so that the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset abnormal time is not specifically limited, and a person skilled in the art can freely set the preset abnormal time only by meeting the value requirement of the preset abnormal time, wherein when the monitoring period is 7 days, the optimal value of the preset abnormal time is 1h.
Specifically, the adjusting unit compares the length f0 of the climbing road section in the monitoring period with the preset length f1, and adjusts the analysis process of the abnormal state of the battery pack according to the comparison result, wherein:
When f0 is less than or equal to f1, the adjusting unit judges that the length of the climbing road section is normal, and no adjustment is performed;
when f0 > f1, the adjusting unit judges that the length of the climbing road section is abnormal, sets an adjusting coefficient alpha to adjust the analysis process of the abnormal state of the battery pack, and sets alpha=e 3(f0-f1)/f0-3 The adjusted preset abnormal time is set to D0', and D0' =d0×α is set.
Specifically, the adjusting unit improves the accuracy of the adjusting coefficient by setting the preset length, and further improves the accuracy of analysis of abnormal time of the state of the battery pack, so that the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset length is not specifically limited, and a person skilled in the art can freely set the preset length only by meeting the value requirement of the preset length, wherein when the monitoring period is 7 days, the optimal value of f1 is 3km.
Specifically, the parameter analysis unit analyzes the obtained internal resistance n1, the battery capacity m1, the initial internal resistance n0, and the initial capacity m0 of the battery, wherein:
when (n 0-n 1)/n 0 is less than or equal to e1, the parameter analysis unit judges that the internal resistance of the battery pack is normal; when (n 0-n 1)/n 0 > e1, the parameter analysis unit determines that the internal resistance of the battery pack is abnormal;
When (m 0-m 1)/m 0 is less than or equal to e2, the parameter analysis unit judges that the capacity of the battery pack is normal; when (m 0-m 1)/m 0 > e2, the parameter analysis unit determines that the battery pack capacity is abnormal;
wherein e1 is a first aging threshold, and e2 is a second aging threshold.
Specifically, the parameter analysis unit improves the accuracy of parameter analysis by setting a preset aging threshold value, so that the accuracy of battery pack aging degree analysis is improved, the management efficiency of the battery pack charging depth is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset aging threshold is not specifically limited, and a person skilled in the art can freely set the setting of the preset aging threshold only by meeting the value requirement of the preset aging threshold, wherein the optimal value of e1 is 0.1, and the optimal value of e2 is 0.12.
Specifically, the aging degree analysis unit analyzes the aging degree of the battery pack according to the analysis result of the battery pack parameter, wherein:
when the internal resistance of the battery pack is normal and the capacity of the battery pack is normal, the aging degree analysis unit sets the aging degree of the battery pack to L1, and sets l1=0;
when the internal resistance of the battery is abnormal and the capacity of the battery is normal, the aging degree analysis unit sets the aging degree of the battery to L2, and sets l2=0.6xsin [ (n 0-n 1)/n 0 x (pi/2) ];
When the internal resistance of the battery is normal and the capacity of the battery is abnormal, the aging degree analysis unit sets the aging degree of the battery to L3, and sets l3=0.4× [ (n 0-n 1)/n 0-e1 ]/(n 0-n 1)/n 0;
when the internal resistance of the battery is abnormal and the capacity of the battery is abnormal, the aging degree analysis unit sets the aging degree of the battery to L4, and sets l4=0.6xsin [ (n 0-n 1)/n0× (pi/2) ]+0.4× [ (n 0-n 1)/n 0-e1 ]/(n 0-n 1)/n 0.
Specifically, the correction unit will manage the ambient temperature t0 within a period i Comparing the aging degree of the battery pack with each preset temperature, and correcting the aging degree of the battery pack according to the comparison result, wherein:
when t0 i T1 or t0 is less than or equal to i When the temperature is not less than t2, the correction unit judges that the ambient temperature is abnormal;
when t1 < t0 i When the temperature is less than t2, the correction unit judges that the ambient temperature is normal;
the correction unit sets the number of abnormal ambient temperature times in the management period as r, sets a correction coefficient Y to correct the analysis process of the aging degree of the battery pack, and sets Y=1+2/pi×arctan [ r/2T×pi ]]The aging degree L of the battery pack after correction R Let L be R ' set L R ’=L R ×Y，R=1,2,3,4，t0 i For the ambient temperature of the ith day in the management period, i is more than 0 and less than or equal to T, T is the number of days in the management period, T1 is the preset minimum temperature, and T2 is the preset maximum temperature.
Specifically, the correction unit improves the accuracy of the correction coefficient by setting the preset temperature, so that the accuracy of the aging degree analysis of the battery pack is improved, the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset temperature is not specifically limited, and a person skilled in the art can freely set the setting of the preset temperature only by meeting the value requirement of the preset temperature, wherein the optimal value of t1 is-5 ℃, and the optimal value of t2 is 36 ℃.
Specifically, the compensation unit compares the acquired altitude h0 with a preset altitude h1, and compensates a correction process of the battery pack aging degree analysis process according to a comparison result, wherein:
when h0 is less than or equal to h1, the compensation unit judges that the altitude is normal and does not compensate;
when h0 > h1, the compensation unit determines that the altitude is abnormal, and sets a compensation coefficient Z to compensate for the correction process of the battery pack aging analysis process, and z=1+ (h0-h 1)/(h0+h1).
Specifically, the compensation unit improves the accuracy of the compensation coefficient by setting the preset altitude, so that the accuracy of the aging degree analysis of the battery pack is improved, the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset altitude is not specifically limited, and a person skilled in the art can freely set the preset altitude only by meeting the value requirement of the preset altitude, wherein the optimal value of h1 is 4800m.
Specifically, the charging depth management module manages the lowest charging depth of the battery pack in the next monitoring period according to the analysis result of the abnormal time of the battery pack in the monitoring period and the aging degree of the battery pack, wherein:
when the battery voltage abnormality time is normal and the battery current abnormality time is normal and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q1, and sets Q1=q0× {1+w1×sin [ L ] R ×(π/2)]};
When the battery voltage abnormality time is long and the battery current abnormality time is normal and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q2, and sets Q2=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is long and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q3, and sets Q3=q0× {1+w1×sin [ L ] R ×(π/2)]+w3×(d2-d0)/(d2+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is normal and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q4, and sets Q4=q0× {1+w1×sin [ L ] R ×(π/2)]+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is long and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q5, and sets Q4=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w3×(d2-d0)/(d2+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is normal and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q6, and sets Q6=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is long and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q7, and sets Q7=q0× {1+w1×sin [ L ] R ×(π/2)]+w3×(d2-d0)/(d2+d0)+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is long and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q8, and sets Q8=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w3×(d2-d0)/(d2+d0)+w4×(d3-d0)/(d3+d0)};
The charging depth management module analyzes the analysis result Q of the lowest charging depth u Outputting to a user;
wherein u=1, 2..8, w1 is the age weight, w2 is the voltage anomaly weight, w3 is the current anomaly weight, w4 is the temperature anomaly weight, w1+w2+w3+w4=1, w1 > w3 > w2 > w4.
Specifically, the charging depth management module improves the accuracy of analysis of the lowest charging depth of the battery pack by setting the aging degree weight, the voltage abnormality weight, the current abnormality weight and the temperature abnormality weight, so that the management efficiency of the charging depth of the battery pack is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the aging degree weight, the voltage abnormality weight, the current abnormality weight and the temperature abnormality weight is not specifically limited, and can be freely set by a person skilled in the art, and only the values of the aging degree weight, the voltage abnormality weight, the current abnormality weight and the temperature abnormality weight need to be satisfied, wherein the optimal value of w1 is 0.5, the optimal value of w2 is 0.2, the optimal value of w3 is 0.18, and the optimal value of w4 is 0.12.
Specifically, the optimization module compares the aging rate v0 of the battery pack in the current management period with the preset aging rate v1, and optimizes the adjustment process of the state anomaly time analysis process of the battery pack in the next management period according to the comparison result, wherein:
when v0 is less than or equal to v1, the optimization module judges that the aging rate of the battery pack is slow and does not perform optimization;
When v0 > v1, the optimizing module determines that the aging rate of the battery pack is fast, sets an optimizing coefficient beta to optimize the adjusting process of the analysis process of the state anomaly time of the battery pack in the next management period, sets beta=1- (v 0-v 1)/(v0+v1), sets the optimized adjusting coefficient to alpha ', and sets alpha' =alpha×beta.
Specifically, the optimization module improves the accuracy of the optimization coefficient by setting the preset aging rate, and further improves the accuracy of analysis of abnormal time of the battery pack state, so that the management efficiency of the battery pack charging depth is improved, the management efficiency of the battery pack is finally improved, and the service life of the battery pack is prolonged; in this embodiment, the setting of the preset aging rate is not specifically limited, and a person skilled in the art can freely set the setting of the preset aging rate only by meeting the value requirement of the preset aging rate, wherein the optimal value of v1 is 0.028%/day.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
Claims (10)
1. A safety supervision system for a battery pack of a hybrid electric vehicle is characterized by comprising,
the information acquisition module is used for acquiring battery pack information, vehicle information, road condition information and environment information;
the state monitoring module is used for analyzing the state of the battery pack according to the acquired battery pack voltage, battery pack current and battery pack temperature and carrying out abnormal early warning according to an analysis result;
the state analysis module is used for acquiring voltage early warning time, current early warning time and temperature early warning time in the monitoring period, analyzing the state abnormal time of the battery pack according to the voltage early warning time, the current early warning time and the temperature early warning time in the monitoring period, and adjusting the analysis process of the state abnormal time of the battery pack according to the length of a climbing road section in the monitoring period;
the aging degree analysis module is used for analyzing the aging degree of the battery pack according to the acquired internal resistance and capacity of the battery pack;
the correction module is used for correcting the analysis process of the aging degree of the battery pack according to the acquired environmental temperature and the altitude of the management period, is provided with a correction unit used for correcting the analysis process of the aging degree of the battery pack according to the acquired environmental temperature of the management period, and is also provided with a compensation unit used for compensating the correction process of the analysis process of the aging degree of the battery pack according to the acquired altitude;
The charging depth management module is used for managing the lowest charging depth of the battery pack in the next monitoring period according to the analysis result of the state abnormal time of the battery pack in the monitoring period and the analysis result of the aging degree of the battery pack;
and the optimization module is used for optimizing the adjustment process of the analysis process of the abnormal state of the battery pack in the next management period according to the aging rate of the battery pack in the current management period.
2. The hybrid vehicle battery pack safety supervision system according to claim 1, wherein the state monitoring module is provided with a voltage analysis unit, the voltage analysis unit compares the acquired battery pack voltage a0 with each preset voltage, and analyzes the voltage state of the battery pack according to the comparison result, wherein:
when a0 is less than or equal to a1 or a0 is more than or equal to a2, the voltage analysis unit judges that the voltage of the battery pack is abnormal and performs voltage early warning;
when a1 is more than a0 and less than a2, the voltage analysis unit judges that the voltage of the battery pack is normal and does not perform early warning; wherein a1 is a preset minimum voltage, and a2 is a preset maximum voltage;
the state monitoring module is also provided with a current analysis unit, the current analysis unit compares the acquired battery current b0 with each preset current and analyzes the current state of the battery according to the comparison result, wherein:
When b0 is less than or equal to b1 or b0 is more than or equal to b2, the current analysis unit judges that the current of the battery pack is abnormal and performs current abnormality early warning;
when b1 is more than b0 and less than b2, the current analysis unit judges that the current of the battery pack is normal, and early warning is not carried out; wherein b1 is a preset minimum current, and b2 is a preset maximum current;
the state monitoring module is also provided with a temperature analysis unit, the temperature analysis unit compares the acquired battery pack temperature c0 with each preset temperature and analyzes the temperature state of the battery pack according to the comparison result, wherein:
when c0 is less than or equal to c1 or c0 is more than or equal to c2, the temperature analysis unit judges that the temperature of the battery pack is abnormal and performs temperature abnormality early warning;
when c1 is more than c0 and less than c2, the temperature analysis unit judges that the temperature of the battery pack is normal, and early warning is not carried out; wherein c1 is the minimum preset temperature, and c2 is the maximum preset temperature.
3. The hybrid vehicle battery pack safety supervision system according to claim 2, wherein the state analysis module is provided with a state analysis unit, the state analysis unit compares the voltage early-warning time D1, the current early-warning time D2 and the temperature early-warning time D3 in the monitoring period with a preset abnormal time D0 respectively, and analyzes the state abnormal time of the battery pack according to the comparison result, wherein:
When D1 is less than or equal to D0, the state analysis unit judges that the abnormal time of the battery pack voltage in the monitoring period is normal, and when D1 is more than D0, the state analysis unit judges that the abnormal time of the battery pack voltage in the monitoring period is long, and outputs the abnormal time of the battery pack voltage to a user;
when D2 is less than or equal to D0, the state analysis unit judges that the abnormal time of the battery current in the monitoring period is normal, and when D2 is more than D0, the state analysis unit judges that the abnormal time of the battery current in the monitoring period is long and outputs the abnormal time of the battery current to a user;
when D3 is less than or equal to D0, the state analysis unit judges that the temperature abnormality time of the battery pack in the monitoring period is normal, and when D3 is more than D0, the state analysis unit judges that the temperature abnormality time of the battery pack in the monitoring period is long, and outputs the temperature abnormality time of the battery pack to a user.
4. The hybrid vehicle battery pack safety supervision system according to claim 3, wherein the state analysis module is further provided with an adjustment unit, the adjustment unit compares a climbing road section length f0 in a monitoring period with a preset length f1, and adjusts an analysis process of an abnormal state of the battery pack according to a comparison result, wherein:
When f0 is less than or equal to f1, the adjusting unit judges that the length of the climbing road section is normal, and no adjustment is performed;
when f0 > f1, the adjusting unit judges that the length of the climbing road section is abnormal, sets an adjusting coefficient alpha to adjust the analysis process of the abnormal state of the battery pack, and sets alpha=e 3(f0-f1)/f0-3 The adjusted preset abnormal time is set to D0', and D0' =d0×α is set.
5. The hybrid vehicle battery pack safety supervision system according to claim 1, wherein the aging degree analysis module is provided with a parameter analysis unit that analyzes parameters of the battery pack with respect to the acquired internal resistance n1 of the battery pack, the battery pack capacity m1, the battery pack initial internal resistance n0, and the battery pack initial capacity m0, wherein:
when (n 0-n 1)/n 0 is less than or equal to e1, the parameter analysis unit judges that the internal resistance of the battery pack is normal;
when (n 0-n 1)/n 0 > e1, the parameter analysis unit determines that the internal resistance of the battery pack is abnormal;
when (m 0-m 1)/m 0 is less than or equal to e2, the parameter analysis unit judges that the capacity of the battery pack is normal; when (m 0-m 1)/m 0 > e2, the parameter analysis unit determines that the battery pack capacity is abnormal.
6. The hybrid vehicle battery pack safety supervision system according to claim 5, wherein the aging degree analysis module is further provided with an aging degree analysis unit that analyzes the aging degree of the battery pack according to an analysis result of the battery pack parameter, wherein:
When the internal resistance of the battery pack is normal and the capacity of the battery pack is normal, the aging degree analysis unit sets the aging degree of the battery pack to L1, and sets l1=0;
when the internal resistance of the battery is abnormal and the capacity of the battery is normal, the aging degree analysis unit sets the aging degree of the battery to L2, and sets l2=0.6xsin [ (n 0-n 1)/n 0 x (pi/2) ];
when the internal resistance of the battery is normal and the capacity of the battery is abnormal, the aging degree analysis unit sets the aging degree of the battery to L3, and sets l3=0.4× [ (n 0-n 1)/n 0-e1 ]/(n 0-n 1)/n 0;
when the internal resistance of the battery is abnormal and the capacity of the battery is abnormal, the aging degree analysis unit sets the aging degree of the battery to L4, and sets l4=0.6xsin [ (n 0-n 1)/n0× (pi/2) ]+0.4× [ (n 0-n 1)/n 0-e1 ]/(n 0-n 1)/n 0.
7. The hybrid vehicle battery pack safety supervision system according to claim 6, wherein the correction unit is to manage the ambient temperature t0 during the period i Comparing the aging degree of the battery pack with each preset temperature, and correcting the aging degree of the battery pack according to the comparison result, wherein:
when t0 i T1 or t0 is less than or equal to i When the temperature is not less than t2, the correction unit judges that the ambient temperature is abnormal;
when t1 < t0 i When the temperature is less than t2, the correction unit judges that the ambient temperature is normal;
The correction unit sets the number of abnormal ambient temperature times in the management period as r, sets a correction coefficient Y to correct the analysis process of the aging degree of the battery pack, and sets Y=1+2/pi×arctan [ r/2T×pi ]]The aging degree L of the battery pack after correction R Let L be R ' set L R ’=L R ×Y，R=1,2,3,4，t0 i Is a tubeThe ambient temperature of the ith day in the management period is more than 0 and less than or equal to T, T is the number of days in the management period, T1 is the preset minimum temperature, and T2 is the preset maximum temperature.
8. The hybrid vehicle battery pack safety supervision system according to claim 7, wherein the compensation unit compares the acquired altitude h0 with a preset altitude h1, and compensates a correction process of the battery pack aging degree analysis process according to the comparison result, wherein:
when h0 is less than or equal to h1, the compensation unit judges that the altitude is normal and does not compensate;
when h0 > h1, the compensation unit determines that the altitude is abnormal, and sets a compensation coefficient Z to compensate for the correction process of the battery pack aging analysis process, and z=1+ (h0-h 1)/(h0+h1).
9. The hybrid vehicle battery pack safety supervision system according to claim 1, wherein the depth of charge management module manages a lowest depth of charge of the battery pack for a next monitoring period from an analysis result of a battery pack anomaly time and an aging degree of the battery pack in the monitoring period, wherein:
When the battery voltage abnormality time is normal and the battery current abnormality time is normal and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q1, and sets Q1=q0× {1+w1×sin [ L ] R ×(π/2)]};
When the battery voltage abnormality time is long and the battery current abnormality time is normal and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q2, and sets Q2=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is long and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q3, and sets Q3=q0× {1+w1×sin [ L ] R ×(π/2)]+w3×(d2-d0)/(d2+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is normal and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q4, and sets Q4=q0× {1+w1×sin [ L ] R ×(π/2)]+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is long and the battery temperature abnormality time is normal, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q5, and sets Q4=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w3×(d2-d0)/(d2+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is normal and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q6, and sets Q6=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is normal and the battery current abnormality time is long and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q7, and sets Q7=q0× {1+w1×sin [ L ] R ×(π/2)]+w3×(d2-d0)/(d2+d0)+w4×(d3-d0)/(d3+d0)};
When the battery voltage abnormality time is long and the battery current abnormality time is long and the battery temperature abnormality time is long, the charging depth management module sets the lowest charging depth of the battery in the next monitoring period to be Q8, and sets Q8=q0× {1+w1×sin [ L ] R ×(π/2)]+w2×(d1-d0)/(d1+d0)+w3×(d2-d0)/(d2+d0)+w4×(d3-d0)/(d3+d0)};
The charging depth management module analyzes the analysis result Q of the lowest charging depth u Outputting to a user;
wherein u=1, 2..8, w1 is the age weight, w2 is the voltage anomaly weight, w3 is the current anomaly weight, w4 is the temperature anomaly weight, w1+w2+w3+w4=1, w1 > w3 > w2 > w4.
10. The hybrid vehicle battery pack safety supervision system according to claim 5, wherein the optimization module compares an aging rate v0 of the battery pack in a current management cycle with a preset aging rate v1, and optimizes an adjustment process of a state anomaly time analysis process of the battery pack in a next management cycle according to a comparison result, wherein:
When v0 is less than or equal to v1, the optimization module judges that the aging rate of the battery pack is slow and does not perform optimization;
when v0 > v1, the optimizing module determines that the aging rate of the battery pack is fast, sets an optimizing coefficient beta to optimize the adjusting process of the analysis process of the state anomaly time of the battery pack in the next management period, sets beta=1- (v 0-v 1)/(v0+v1), sets the optimized adjusting coefficient to alpha ', and sets alpha' =alpha×beta.
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