A method for output stability testing of a hybrid system
Patent Information
- Application Number
- CN202611395739.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-09-09
- Publication Date
- 2026-10-13
AI Technical Summary
现有的测试方法没有在识别能量耦合共振的基础上提取功率和转速的波动主频，也未建立波动主频特征与机械惯量响应特性之间的量化关系
通过输出功率波动序列和输出转速波动序列，在时间轴上标定输出功率波动特征点和输出转速波动特征点，并计算两类特征点之间的时间轴重合度。功率波动特征点和转速波动特征点分别对应功率变化率和转速变化率由正转负的拐点，这些拐点标识了波动从上升转为下降的相位转折位置。当功率下降拐点与转速下降拐点在时间轴上大量重合或紧密相邻时，表明功率波动与转速波动的相位变化高度同步，这是能量耦合共振的典型时间域特征。通过统计重合特征点数量和邻近特征点数量，计算包含初始重合率和附加重合率的时间轴重合度，可以在波动的幅值尚未超出稳态限值时，从相位同步角度提前发现系统是否进入能量耦合共振状态，克服了常规测试方法仅依赖幅值阈值判断而无法反映功率与转速之间动态时序关系的不足。在确定混合动力系统处于能量耦合共振状态后，截取共振时间区间内的输出功率波动序列和输出转速波动序列，通过极值点识别提取功率波动主频和转速波动主频，并利用两个主频的频率比值与动力耦合装置的机械惯量基准值计算机械惯量响应系数。频率比值反映了功率波动频率与转速波动频率在共振状态下的相对跟随特性，当频率比值偏离理想耦合关系时，表明系统的旋转惯量与电气响应时间常数之间出现动态失配。将频率比值乘以由齿轮齿数比和轴系刚度计算得到的机械惯量基准值，得到机械惯量响应系数，该系数将频率域的波动特征映射为物理惯量响应特性参数。通过将机械惯量响应系数划分为多个区间，对应惯量匹配稳定级、惯量欠匹配临界级和惯量失配振荡级，可以在识别共振状态后进一步量化评定系统的输出稳定性等级，为调整电机控制参数或修正动力耦合装置匹配关系提供直接依据。
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Abstract
Description
Technical Field
[0001] This invention relates to the field of hybrid power system testing technology, specifically to a method for testing the output stability of hybrid power systems. Background Technology
[0002] During operation, a hybrid power system involves torque superposition and speed transmission between the engine and motor via a power coupling device. The energy flow between these multiple power sources influences each other, resulting in periodic or non-periodic fluctuations in output power and speed. When power and speed fluctuations synchronize over time, the system may enter an energy-coupled resonance state. This state amplifies torsional vibrations in the mechanical transmission chain, affecting the smoothness of power output. Existing hybrid power system output stability testing methods primarily focus on the mean deviation of power and speed under steady-state conditions, determining whether the system meets factory requirements by setting allowable fluctuation ranges for output power and speed. These methods only limit fluctuations in amplitude and cannot reflect the temporal correlation between power and speed fluctuations. In the energy-coupled resonance state, the amplitude of power and speed fluctuations may still be within the allowable range, but their fluctuation characteristics highly overlap over time. The impact load on the mechanical transmission system continuously accumulates, leading to accelerated wear of the power coupling device and decreased transmission efficiency. Due to the lack of detection methods for the time alignment of power fluctuations and speed fluctuations, existing technologies struggle to detect energy coupling resonance trends before the system exhibits significant out-of-tolerance behavior, and are also unable to perform refined classification of output stability based on the degree of inertia matching.
[0003] When a specific proportional relationship exists between the dominant frequency of power fluctuations and the dominant frequency of speed fluctuations, it indicates a dynamic coupling mismatch between the mechanical inertia and the electronic control strategy of the hybrid power system. Existing testing methods do not extract the dominant frequencies of power and speed fluctuations based on identifying energy coupling resonance, nor do they establish a quantitative relationship between the characteristics of the dominant frequency fluctuations and the mechanical inertia response characteristics. This raises two issues that need to be addressed: first, how to capture the energy coupling resonance state through the coincidence characteristics of power and speed fluctuations on the time axis; and second, after determining that the system is in a resonance state, how to construct a response coefficient reflecting the degree of mechanical inertia matching using the dominant frequencies of power and speed fluctuations, and thereby classify the output stability. Summary of the Invention
[0004] This invention provides a method for testing the output stability of a hybrid power system. It aims to identify the energy coupling resonance state of the hybrid power system by calculating the time axis coincidence of the characteristic points of output power fluctuation and the characteristic points of output speed fluctuation, and to calculate the mechanical inertia response coefficient using the dominant frequency of power fluctuation and the dominant frequency of speed fluctuation in the resonance state, thereby achieving a graded evaluation of output stability.
[0005] To achieve the above objectives, the present invention provides the following technical solution: The present invention provides a method for testing the output stability of a hybrid power system, which achieves accurate identification of the energy coupling resonance state and precise evaluation of the output stability level by real-time monitoring and linkage analysis of the output power and output speed of the hybrid power system.
[0006] This method first calculates the output power fluctuation sequence and the output speed fluctuation sequence based on the real-time output power and real-time output speed of the hybrid power system. Preferably, real-time output power and real-time output speed are continuously collected at a fixed sampling period to construct original power time series and original speed time series, respectively. A sliding window differencing operation is performed on the original power time series to calculate the instantaneous power change rate at each sampling moment. The instantaneous power change rates at all sampling moments are arranged in chronological order to obtain the output power fluctuation sequence. Similarly, a sliding window differencing operation is performed on the original speed time series to calculate the instantaneous speed change rate at each sampling moment. The instantaneous speed change rates at all sampling moments are arranged in chronological order to obtain the output speed fluctuation sequence. Through sliding window differencing, the dynamic fluctuation components of power and speed can be effectively extracted, providing a highly sensitive fluctuation characterization for subsequent feature point calibration.
[0007] Based on the obtained fluctuation sequence, characteristic points of output power fluctuation and output speed fluctuation are marked on the time axis according to the output power fluctuation sequence and the output speed fluctuation sequence. As a preferred embodiment of the invention, the sampling moment when the instantaneous power change rate switches from a positive value to a negative value is marked as the power decrease inflection point, and all power decrease inflection points are used as output power fluctuation characteristic points; similarly, the sampling moment when the instantaneous speed change rate switches from a positive value to a negative value is marked as the speed decrease inflection point, and all speed decrease inflection points are used as output speed fluctuation characteristic points. Furthermore, a hysteresis threshold can be introduced, and the sampling moment when the instantaneous power change rate switches from a positive value to a negative value and the absolute value of the change rate is greater than a preset hysteresis threshold is marked as the power decrease inflection point, thereby filtering out minor noise interference and improving the anti-interference capability of the characteristic point marking. These decreasing inflection points centrally reflect the key moments of energy release, providing a clear comparison benchmark for the time correlation analysis between power and speed fluctuations.
[0008] Next, the time axis overlap between the output power fluctuation feature points and the output speed fluctuation feature points is calculated. In this calculation, the total number of output power fluctuation feature points is first counted, and the number of feature points that overlap with any output speed fluctuation feature point at the same sampling time is also counted. This overlap is divided by the total number of output power fluctuation feature points to obtain the initial overlap rate. Then, the number of remaining feature points that do not overlap with the output power fluctuation feature points is counted, and the number of neighboring feature points whose time interval with their nearest neighbor is less than a preset threshold is also counted. This neighboring feature point count is divided by the total number of output power fluctuation feature points to obtain the additional overlap rate. Finally, the initial overlap rate and the additional overlap rate are added together to obtain the time axis overlap. This overlap calculation method not only considers strictly synchronized falling inflection points but also takes into account feature points that appear successively within a very short time difference, thus more comprehensively reflecting the temporal coupling degree of power fluctuations and speed fluctuations and improving the ability to identify weakly coupled states.
[0009] When the time axis overlap exceeds a preset overlap threshold, the hybrid power system is determined to be in an energy-coupled resonance state, and the dominant frequencies of power fluctuations and speed fluctuations in this state are obtained. Specifically, the output power fluctuation sequence within the time interval corresponding to the energy-coupled resonance state is extracted. Extreme points of the instantaneous power change rate within this time interval are identified in chronological order. The instantaneous power change rate values and occurrence times corresponding to all maximum points are extracted. The time difference between the occurrence times of two adjacent maximum points is calculated, and the average of all time differences is obtained to obtain the dominant frequency of power fluctuations. The output speed fluctuation sequence is processed in the same way to obtain the dominant frequency of speed fluctuations. The criterion for extreme point identification can be set to the instantaneous change rate value at the current moment being greater than the instantaneous change rate values at both the previous and next sampling moments. By locking the energy-coupled resonance interval and extracting the dominant frequency, the core frequency characteristics of the interactive oscillation between electrical and mechanical energy in the hybrid power system can be directly obtained, providing accurate frequency domain input for subsequent inertial response analysis.
[0010] The mechanical inertia response coefficient of the hybrid power system is calculated based on the dominant frequencies of power fluctuation and speed fluctuation. Preferably, the frequency ratio between the dominant power fluctuation frequency and the dominant speed fluctuation frequency is calculated. A reference value for the mechanical inertia of the hybrid power system is determined based on the number of gear teeth and shaft stiffness of the power coupling device. For example, the reference value for mechanical inertia can be obtained by multiplying the gear tooth ratio of the power coupling device by the square root of the shaft stiffness. The mechanical inertia response coefficient is obtained by multiplying the frequency ratio by the reference value for mechanical inertia. This coefficient integrates the system's inherent inertia parameters with the actual oscillation frequency characteristics, and can quantitatively characterize the actual contribution of mechanical inertia to output stability under energy coupling resonance conditions. The magnitude of the coefficient directly reflects the system's inertia matching status.
[0011] Finally, the output stability of the hybrid power system is graded based on the mechanical inertia response coefficient. The range of the mechanical inertia response coefficient is divided into three intervals, from smallest to largest, with the upper limit of the first interval lower than the lower limit of the second interval, and vice versa. When the mechanical inertia response coefficient falls within the first interval, the output stability of the hybrid power system is marked as inertia-matched stability, indicating good matching between mechanical inertia and electrical characteristics, and stable system output. When the mechanical inertia response coefficient falls within the second interval, the output stability is marked as inertia-mismatch critical level, indicating that the system is approaching the edge of resonance instability and requires attention to operating conditions. When the mechanical inertia response coefficient falls within the third interval, the output stability is marked as inertia-mismatch oscillation level, indicating severe inertia mismatch and a risk of large-scale oscillations in the system. This grading mechanism provides direct decision-making basis for the state monitoring, early warning, and active control of the hybrid power system, significantly improving the engineering practicality of the test.
[0012] The technical effects and advantages provided by the present invention in the above technical solution are as follows: By using output power fluctuation sequences and output speed fluctuation sequences, characteristic points of output power fluctuation and output speed fluctuation are marked on the time axis, and the time axis overlap between the two types of characteristic points is calculated. The power fluctuation characteristic points and speed fluctuation characteristic points correspond to the inflection points where the power change rate and speed change rate change change from positive to negative, respectively. These inflection points mark the phase transition positions where the fluctuations change from rising to falling. When the power decrease inflection point and the speed decrease inflection point largely overlap or are closely adjacent on the time axis, it indicates that the phase changes of power fluctuation and speed fluctuation are highly synchronized, which is a typical time-domain characteristic of energy coupling resonance. By statistically analyzing the number of overlapping characteristic points and the number of adjacent characteristic points, the time axis overlap, including the initial overlap rate and the additional overlap rate, is calculated. This allows for early detection of whether the system has entered an energy coupling resonance state from a phase synchronization perspective, before the fluctuation amplitude exceeds the steady-state limit. This overcomes the shortcomings of conventional testing methods that rely solely on amplitude thresholds and cannot reflect the dynamic temporal relationship between power and speed. After determining that the hybrid power system is in an energy coupling resonance state, the output power fluctuation sequence and output speed fluctuation sequence within the resonance time interval are extracted. The dominant frequencies of power fluctuation and speed fluctuation are extracted by identifying extreme points. The mechanical inertia response coefficient is calculated using the frequency ratio of these two dominant frequencies and the mechanical inertia reference value of the power coupling device. The frequency ratio reflects the relative following characteristics of the power fluctuation frequency and speed fluctuation frequency in the resonance state. When the frequency ratio deviates from the ideal coupling relationship, it indicates a dynamic mismatch between the system's rotational inertia and electrical response time constant. Multiplying the frequency ratio by the mechanical inertia reference value calculated from the gear ratio and shaft stiffness yields the mechanical inertia response coefficient, which maps the frequency domain fluctuation characteristics to physical inertia response characteristic parameters. By dividing the mechanical inertia response coefficient into multiple intervals, corresponding to the inertia matching stable level, the inertia undermatch critical level, and the inertia mismatch oscillation level, the output stability level of the system can be further quantitatively evaluated after identifying the resonance state, providing a direct basis for adjusting motor control parameters or correcting the matching relationship of the power coupling device. Attached Figure Description
[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0014] Figure 1 This is a flowchart of the output stability test method for a hybrid power system; Figure 2 This is a flowchart for calibrating the characteristic points of output power and speed fluctuation in a hybrid power system. Figure 3This is a schematic diagram of the maximum points of the output power fluctuation sequence and the speed fluctuation sequence under the energy coupling resonance state. Detailed Implementation
[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0016] See Figure 1 This invention provides a method for testing the output stability of a hybrid power system. The method includes: calculating an output power fluctuation sequence and an output speed fluctuation sequence based on the real-time output power and real-time output speed of the hybrid power system; marking characteristic points of output power fluctuation and output speed fluctuation on a time axis according to the output power fluctuation sequence and the output speed fluctuation sequence, and calculating the time axis overlap between the characteristic points of output power fluctuation and the characteristic points of output speed fluctuation; determining that the hybrid power system is in an energy coupling resonance state when the time axis overlap is greater than a preset overlap threshold, and obtaining the dominant frequency of power fluctuation and the dominant frequency of speed fluctuation under the energy coupling resonance state; calculating the mechanical inertia response coefficient of the hybrid power system based on the dominant frequency of power fluctuation and the dominant frequency of speed fluctuation; and classifying the output stability of the hybrid power system according to the mechanical inertia response coefficient.
[0017] In specific implementation, please refer to Figure 2 The system collects real-time output power and real-time output speed data from the hybrid power system using a fixed sampling period. The fixed sampling period is determined based on the response bandwidth of the power controller in the hybrid power system, and is for example, set to a constant value within the range of 1 to 10 milliseconds. The output power values collected in chronological order are recorded as the original power time series, and the output speed values collected in the same chronological order are recorded as the original speed time series.
[0018] For the original power time series, the output power fluctuation sequence is obtained through sliding window differencing. The number of sampling points included in the sliding window is set to W, where W is an integer not less than 2. The sliding window moves sequentially from front to back across the original power time series, sampling one point at a time. At each sampling moment... The instantaneous power change rate at that sampling moment is obtained by differential calculation within the sliding window. The calculation method is as follows: ; in, Sampling time The instantaneous power change rate, where W is the number of sampling points included in the sliding window. Sampling time Real-time output power, Sampling time Real-time output power, With a fixed sampling period, i is the summation index, ranging from 0 to W-1. The instantaneous power change rate at all sampling times is arranged in chronological order to obtain the output power fluctuation sequence.
[0019] Optionally, when the sliding window reaches the beginning of the sequence but has not accumulated enough sampling points, all the acquired sampling points are used instead of the complete sliding window for calculation, or the value of W is set to an empirical value that is no greater than the length of the sampling sequence.
[0020] In practice, a sliding window difference operation is also performed on the original rotational speed time series to obtain the output rotational speed fluctuation series. At each sampling time... The instantaneous speed change rate at that sampling moment is obtained by differential calculation within the sliding window. The method used is the same as that used to calculate the instantaneous power change rate, except that the real-time output power is replaced with the real-time output speed. The instantaneous speed change rates at all sampling times are arranged in chronological order to obtain the output speed fluctuation sequence.
[0021] In practical implementation, characteristic points of output power fluctuation and output speed fluctuation are marked on the time axis based on the output power fluctuation sequence and the output speed fluctuation sequence. For the marking of output power fluctuation characteristic points, the output power fluctuation sequence is traversed, and sampling moments where the instantaneous power change rate switches from positive to negative and the absolute value of the change rate is greater than a preset hysteresis threshold are marked as power decline inflection points. All power decline inflection points are used as output power fluctuation characteristic points. The preset hysteresis threshold is used to filter out misjudgments caused by small oscillations of the instantaneous power change rate near zero. The preset hysteresis threshold is taken as a multiple of the standard deviation of the instantaneous power change rate of the hybrid power system under steady-state conditions, for example, 2 to 3 times the standard deviation. When the instantaneous power change rate of a sampling moment is positive, and the instantaneous power change rate of the immediately following sampling moment is negative, and the absolute value of this negative value is greater than the preset hysteresis threshold, the following sampling moment is marked as a power decline inflection point.
[0022] For calibrating the characteristic points of output speed fluctuations, the output speed fluctuation sequence is traversed, and the sampling moment when the instantaneous speed change rate switches from a positive value to a negative value is calibrated as the speed decrease inflection point. All speed decrease inflection points are used as output speed fluctuation characteristic points. When the instantaneous speed change rate of a sampling moment is positive, and the instantaneous speed change rate of the immediately following sampling moment is negative, the following sampling moment is calibrated as the speed decrease inflection point.
[0023] Optionally, during the traversal process, to adapt to different sampling accuracies, when the instantaneous power change rate or instantaneous speed change rate is close to zero and the sign changes at multiple consecutive sampling points, the first sampling moment that satisfies the amplitude condition after the sign changes is selected as the inflection point.
[0024] In practical implementation, the time axis coincidence between the output power fluctuation characteristic points and the output speed fluctuation characteristic points is calculated. First, the total number of output power fluctuation characteristic points is counted, and the total number of output power fluctuation characteristic points is denoted as... The number of characteristic points in the output power fluctuation characteristic points that coincide with any output speed fluctuation characteristic point at the same sampling time is recorded as . Being at the same sampling time means that the sampling time number corresponding to a characteristic point of output power fluctuation is exactly the same as the sampling time number corresponding to a characteristic point of output speed fluctuation.
[0025] The initial overlap rate is calculated by: counting the number of overlapping feature points. Divide by the total number of output power fluctuation characteristic points The initial overlap rate was obtained. Initial overlap rate The value range is between 0 and 1. When all output power fluctuation feature points are at the same sampling time as output speed fluctuation feature points, the initial overlap rate is 1.
[0026] In practical implementation, the number of remaining feature points that do not coincide with the output power fluctuation feature point is counted. The remaining feature points that do not coincide with the output power fluctuation feature point refer to all output speed fluctuation feature points in the set of output speed fluctuation feature points, excluding those sampling points that are already at the same sampling time as the output power fluctuation feature point. The number of remaining feature points is denoted as... For each output speed fluctuation feature point among the remaining feature points, identify the output power fluctuation feature point with the closest time interval to that output speed fluctuation feature point, and calculate the time interval between them. Mark the output speed fluctuation feature points among the remaining feature points whose time interval with the nearest neighboring output power fluctuation feature point is less than a preset interval threshold as neighboring feature points, and count the number of neighboring feature points. The number of neighboring feature points is denoted as [missing information]. The preset interval threshold is set based on the fixed sampling period and the power response lag characteristics of the hybrid power system. The preset interval threshold is set as an integer multiple of the fixed sampling period, with the multiple ranging from 2 to 5 times the fixed sampling period. When the fixed sampling period is 1 millisecond, the preset interval threshold can be set to 3 milliseconds.
[0027] The method for calculating the additional overlap rate is as follows: the number of neighboring feature points... Divide by the total number of output power fluctuation characteristic points The additional overlap rate is obtained. Additional overlap rate This reflects the degree of proximity matching between the characteristic points of output speed fluctuation and the characteristic points of output power fluctuation on the time axis.
[0028] In practice, the time axis overlap is calculated using the following formula: ; in, For time axis overlap, The number of overlapping feature points. This represents the number of neighboring feature points. This represents the total number of characteristic points of output power fluctuation. and The statistical object sets do not overlap, and only one output speed fluctuation feature point is counted. and One of the items is when the output speed fluctuation characteristic point has been included as a characteristic point at the same sampling time as the output power fluctuation characteristic point. When this occurs, it will no longer be included in the statistical scope of neighboring feature points.
[0029] In practical implementation, to obtain the dominant frequency of power fluctuations under the energy-coupled resonance state, the time interval corresponding to the energy-coupled resonance state is first determined. The time interval corresponding to the energy-coupled resonance state begins at the initial sampling time when the time axis overlap is greater than a preset overlap threshold, and ends at the sampling time when the time axis overlap falls back below the preset overlap threshold. The output power fluctuation sequence within this time interval is extracted, and the extracted output power fluctuation sequence contains the instantaneous power change rate at all sampling times within this time interval.
[0030] Extreme points are identified in chronological order of the instantaneous power change rate in the truncated output power fluctuation sequence. The criteria for extreme point identification are: the instantaneous power change rate at the current sampling moment is simultaneously greater than the instantaneous power change rate at the previous sampling moment and the instantaneous power change rate at the next sampling moment. Sampling moments that meet the above criteria are identified as maximum points. During the identification process, when two consecutive sampling moments have equal instantaneous power change rates that are both greater than the instantaneous power change rates at adjacent sampling moments, the earlier sampling moment among the consecutive equal sampling moments is selected as the maximum point.
[0031] Extract the instantaneous power change rate values and occurrence times corresponding to all maxima. The occurrence times are represented by sampling time numbers or actual time values, and the occurrence times of each maxima are arranged in chronological order. Calculate the time difference between the occurrence times of two adjacent maxima, which are defined as two maxima that are immediately adjacent in time. The time difference is the difference between the occurrence times of the later maxima and the occurrence times of the earlier maxima. Averaging the reciprocals of the time differences of all adjacent maxima yields the dominant frequency of the power fluctuation. The dominant frequency of the power fluctuation is calculated using the following formula: ; in, Let m be the dominant frequency of the power fluctuation, m be the total number of maxima identified within the time interval corresponding to the energy coupling resonance state, and u be the index of adjacent maxima pairs, where u is an integer from 1 to m-1. Let be the time difference between the occurrence times of the two adjacent maxima of the u-th pair of adjacent maxima.
[0032] In practice, the dominant frequency of rotational speed fluctuations under the energy-coupled resonance state is obtained using the same method as the dominant frequency of power fluctuations. The output rotational speed fluctuation sequence within the time interval corresponding to the energy-coupled resonance state is extracted. This extracted sequence contains the instantaneous rotational speed change rate at all sampling moments within that time interval. Extreme points are identified in chronological order for the instantaneous rotational speed change rate in the extracted sequence. The criteria for extreme point identification are: the instantaneous rotational speed change rate at the current sampling moment is simultaneously greater than both the instantaneous rotational speed change rate at the previous and subsequent sampling moments. The instantaneous rotational speed change rate and its occurrence time corresponding to all maximum points are extracted. The time difference between the occurrence times of two adjacent maximum points is calculated, and the average of all time differences (take their reciprocals) is taken to obtain the dominant frequency of the rotational speed fluctuation.
[0033] Optionally, during the extreme point identification process, if the total number of maximum points identified within the time interval corresponding to the energy coupling resonance state is less than 3, the time interval is extended to both sides by a preset number of sampling points before the extreme point identification is performed again. The number of extended sampling points shall not exceed 20% of the number of sampling points contained in the original time interval.
[0034] See Figure 3 In the graph, the horizontal axis represents time in milliseconds (ms), the left side of the vertical axis displays the instantaneous power change rate in blue font in kilowatts per second (kW / s), and the right side displays the instantaneous speed change rate in red font in revolutions per minute per second (rpm / s). The solid blue line represents the output power fluctuation sequence, and the dashed red line represents the output speed fluctuation sequence; blue inverted triangles mark the maximum power fluctuation points, and red upright triangles mark the maximum speed fluctuation points.
[0035] As can be observed from the figure, both the power fluctuation sequence and the rotational speed fluctuation sequence exhibit obvious periodic fluctuation characteristics, and the maxima are basically arranged synchronously in time, reflecting their high degree of overlap on the time axis. In the initial stage (approximately 0~200ms), the amplitudes of power and rotational speed fluctuations are large, and the intervals between maxima are uniform, showing typical characteristics of the energy coupling resonance state. As time progresses (approximately 200~600ms), the fluctuation amplitudes gradually weaken, and the distribution density of maxima decreases, reflecting the decay process of the system's energy coupling resonance state.
[0036] In specific implementation, the power fluctuation frequency and speed fluctuation frequency calculated in this embodiment are obtained. The power fluctuation frequency is denoted as... The main frequency of speed fluctuation is denoted as Calculate the frequency ratio between the dominant frequency of power fluctuation and the dominant frequency of speed fluctuation. The frequency ratio is calculated by subtracting the dominant frequency of power fluctuation from the dominant frequency of speed fluctuation. Divide by the main frequency of speed fluctuation The frequency ratio is denoted as .
[0037] In practical implementation, the mechanical inertia reference value of the hybrid power system is determined based on the number of teeth on the gears of the power coupling device and the shaft stiffness. The power coupling device refers to the mechanical transmission device in the hybrid power system that connects the engine output shaft and the electric motor output shaft; it includes a driving gear and a driven gear. The number of teeth on the driving gear of the power coupling device is obtained and denoted as... ; Obtain the number of teeth on the driven gear of the power coupling device, denoted as . The gear ratio is calculated by taking the number of teeth of the driving gear. Divide by the number of teeth on the driven gear The gear ratio is denoted as .
[0038] In practical implementation, the shaft stiffness of the power coupling device is obtained. Shaft stiffness refers to the torsional stiffness of the connecting shafts in the power coupling device. Shaft stiffness is obtained through the design parameters of the hybrid power system or measured using torsional stiffness testing equipment. Shaft stiffness is denoted as... The unit of shaft stiffness is Newton-meters per radian. The square root of the shaft stiffness is calculated and denoted as . .
[0039] The reference value for mechanical inertia is determined by multiplying the gear ratio by the square root of the shaft stiffness. The reference value for mechanical inertia is denoted as... Its dimensions are (Defined by the expression on the right). It should be noted that the "mechanical inertia reference value" in this manual is not a physical quantity in traditional mechanics that characterizes the rotational inertia of an object (its dimension is usually kg·m). 2 Rather, it is a reference parameter defined by the present invention based on the gear ratio and shaft stiffness of the dynamic coupling device, used to quantify the response characteristics of a mechanical system, and its dimensions are determined by the expression. The mechanical inertia reference value is calculated using the following formula: ; in, As the reference value for mechanical inertia, The number of teeth on the driving gear of the power coupling device. The number of teeth on the driven gear of the power coupling device. The shaft stiffness of the dynamic coupling device.
[0040] In practical implementation, the frequency ratio Multiply by the mechanical inertia reference value The characteristic value of the mechanical inertia response is obtained. The characteristic value of the mechanical inertia response is denoted as... Its dimensions are The mechanical inertia response coefficient is calculated as follows: Mechanical inertia response eigenvalues This reflects the quantitative result of the frequency relationship between the output power fluctuation and the output speed fluctuation of the hybrid power system under the energy coupling resonance state, after correction by mechanical structure parameters.
[0041] In specific implementation, the mechanical inertia response coefficient calculated in this embodiment is obtained, and the mechanical inertia response characteristic value is denoted as... The range of values for the mechanical inertia response coefficient is divided into three intervals, namely, the first interval, the second interval, and the third interval, in ascending order of numerical value. The upper limit of the first interval is lower than the lower limit of the second interval, and the upper limit of the second interval is lower than the lower limit of the third interval. The boundary values of the three intervals are determined by the statistical distribution of the mechanical inertia response coefficient calibrated by the hybrid power system under standard test conditions.
[0042] In practice, the boundary values for the first, second, and third intervals are determined as follows: Multiple output stability tests are conducted on the same model of hybrid power system under standard test conditions. The mechanical inertia response coefficients corresponding to each test are obtained, constructing a sample set of mechanical inertia response coefficients. The mechanical inertia response coefficients in the sample set are then sorted, and the lower quartile of the sample set is calculated. The lower quartile is denoted as [the lower quartile is not specified in the original text]. ; Calculate the upper quartile of the sample set, denoted as . The lower and upper quartiles are calculated as follows: All mechanical inertia response coefficients in the sample set are arranged in ascending order of value, and the value at the 25th percentile is taken as the lower quartile. The value at the 75th percentile after permutation is taken as the upper quartile. .
[0043] In practice, the upper limit of the first interval is set as the lower quartile. The range of values in the first interval is less than or equal to The second interval is defined as having a lower limit greater than the lower quartile. The upper limit of the second interval is set as the upper quartile. The range of values in the second interval is greater than and less than or equal to The interval. The lower limit of the third interval is set to be greater than the upper quartile. The range of values in the third interval is greater than The range.
[0044] Optionally, the boundary values for the first, second, and third intervals can also be determined through theoretical calculations during the design phase. When the gear ratio of the hybrid power system is denoted as... Shaft stiffness is denoted as At that time, the theoretical value of the upper limit of the first interval is the mechanical inertia reference value. Multiply by the first coefficient The theoretical value of the upper limit of the second interval is the mechanical inertia reference value. Multiply by the second coefficient The first coefficient The value range is from 0.8 to 1.0, the second coefficient The value ranges from 1.2 to 1.5, and the specific value is determined based on the allowable power fluctuation tolerance and allowable speed fluctuation tolerance of the hybrid power system.
[0045] In practical implementation, when classifying the output stability of a hybrid power system, the mechanical inertia response characteristic value is used. The values are compared with those in the first, second, and third intervals. When the mechanical inertia response coefficient falls into the first interval, the output stability of the hybrid power system is marked as the inertia matching stability level. The inertia matching stability level indicates that the mechanical inertia response characteristics of the hybrid power system are within the design expectation range, and the dynamic matching relationship between output power and output speed is stable.
[0046] When the mechanical inertia response coefficient falls into the second interval, the output stability of the hybrid power system is marked as the critical level of inertia undermatch. The critical level of inertia undermatch indicates that the mechanical inertia response characteristics of the hybrid power system deviate from the design expectation range but have not yet reached the level of instability and oscillation. Under certain operating conditions, the hybrid power system may experience short-term mismatch between output power and output speed.
[0047] When the mechanical inertia response coefficient falls into the third interval, the output stability of the hybrid power system is marked as an inertia mismatch oscillation level. An inertia mismatch oscillation level indicates that the mechanical inertia response characteristics of the hybrid power system significantly deviate from the design expectation range, indicating a continuous risk of energy coupling oscillations and that the output stability does not meet the usage requirements.
[0048] Optionally, the stability grading results can be output via the hybrid system's onboard display or transmitted to external diagnostic equipment via a diagnostic communication interface. The grading results, along with the hybrid system's operating status data, are recorded to determine the hybrid system's maintenance strategy.
[0049] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.
Claims
1. A method for testing the output stability of a hybrid power system, characterized in that, include: Based on the real-time output power and real-time output speed of the hybrid power system, the output power fluctuation sequence and the output speed fluctuation sequence are calculated. Based on the output power fluctuation sequence and the output speed fluctuation sequence, mark the output power fluctuation feature points and the output speed fluctuation feature points on the time axis, and calculate the time axis overlap between the output power fluctuation feature points and the output speed fluctuation feature points; When the time axis overlap is greater than a preset overlap threshold, it is determined that the hybrid power system is in an energy coupling resonance state, and the power fluctuation main frequency and speed fluctuation main frequency in the energy coupling resonance state are obtained. Calculate the mechanical inertia response coefficient of the hybrid power system based on the power fluctuation frequency and the speed fluctuation frequency. The output stability of the hybrid power system is graded based on the mechanical inertia response coefficient.
2. The method for testing the output stability of a hybrid power system according to claim 1, characterized in that, The steps for calculating the output power fluctuation sequence and output speed fluctuation sequence based on the real-time output power and real-time output speed of the hybrid power system specifically include: The real-time output power and real-time output speed of the hybrid power system are continuously collected according to a fixed sampling period, and the original power time series and the original speed time series are constructed respectively. The original power time series is subjected to sliding window difference operation to calculate the instantaneous power change rate at each sampling time. The instantaneous power change rates at all sampling times are arranged in chronological order to obtain the output power fluctuation sequence. A sliding window difference operation is performed on the original rotational speed time series to calculate the instantaneous rotational speed change rate at each sampling moment. The instantaneous rotational speed change rates at all sampling moments are arranged in chronological order to obtain the output rotational speed fluctuation sequence.
3. The method for testing the output stability of a hybrid power system according to claim 1, characterized in that, The step of calibrating the characteristic points of output power fluctuation and output speed fluctuation on the time axis based on the output power fluctuation sequence and the output speed fluctuation sequence specifically includes: Traverse the output power fluctuation sequence, mark the sampling moment when the instantaneous power change rate switches from a positive value to a negative value as the power decrease inflection point, and take all power decrease inflection points as the output power fluctuation feature points; Traverse the output speed fluctuation sequence, mark the sampling moment when the instantaneous speed change rate switches from a positive value to a negative value as the speed decrease inflection point, and take all speed decrease inflection points as the output speed fluctuation feature points.
4. The method for testing the output stability of a hybrid power system according to claim 1, characterized in that, The step of calculating the time axis coincidence between the output power fluctuation characteristic point and the output speed fluctuation characteristic point specifically includes: The total number of output power fluctuation feature points is counted, and the number of feature points that overlap with any output speed fluctuation feature point at the same sampling time is counted. The initial overlap rate is obtained by dividing the number of overlapping feature points by the total number of output power fluctuation feature points. The number of remaining feature points that do not overlap with the output power fluctuation feature points among the output speed fluctuation feature points is counted. The number of neighboring feature points among the remaining feature points whose time interval with the nearest neighbor of the output power fluctuation feature point is less than a preset interval threshold is counted. The number of neighboring feature points is divided by the total number of output power fluctuation feature points to obtain the additional overlap rate. The initial overlap rate is added to the additional overlap rate to obtain the time axis overlap degree.
5. The method for testing the output stability of a hybrid power system according to claim 1, characterized in that, The steps for obtaining the dominant frequency of power fluctuation and the dominant frequency of rotational speed fluctuation under the energy coupling resonance state specifically include: The output power fluctuation sequence within the time interval corresponding to the energy coupling resonance state is extracted, and the extreme points of the instantaneous power change rate within the time interval are identified in chronological order. The instantaneous power change rate values and occurrence times corresponding to all maximum points are extracted. Calculate the time difference between the occurrence times of two adjacent maximum points, and then take the average of all time differences after taking their reciprocals to obtain the main frequency of the power fluctuation. The output speed fluctuation sequence within the time interval corresponding to the energy coupling resonance state is extracted, and the extreme points of the instantaneous speed change rate within the time interval are identified in chronological order. The instantaneous speed change rate values and occurrence times corresponding to all maximum points are extracted. Calculate the time difference between the occurrence times of two adjacent maximum points, and then take the average of the reciprocals of all time differences to obtain the main frequency of the rotational speed fluctuation.
6. The method for testing the output stability of a hybrid power system according to claim 1, characterized in that, The step of calculating the mechanical inertia response coefficient of the hybrid power system based on the power fluctuation frequency and the speed fluctuation frequency specifically includes: Calculate the frequency ratio between the power fluctuation frequency and the speed fluctuation frequency; The mechanical inertia reference value of the hybrid power system is determined based on the number of gear teeth and shaft stiffness of the power coupling device in the hybrid power system. The mechanical inertia response coefficient is obtained by multiplying the frequency ratio by the mechanical inertia reference value.
7. The method for testing the output stability of a hybrid power system according to claim 1, characterized in that, The step of classifying the output stability of the hybrid power system based on the mechanical inertia response coefficient specifically includes: The range of values for the mechanical inertia response coefficient is divided into a first interval, a second interval, and a third interval in ascending order of numerical value. The upper limit of the first interval is less than the lower limit of the second interval, and the upper limit of the second interval is less than the lower limit of the third interval. When the mechanical inertia response coefficient falls into the first interval, the output stability of the hybrid power system is marked as the inertia matching stability level; When the mechanical inertia response coefficient falls into the second interval, the output stability of the hybrid power system is marked as the critical level of inertia undermatch. When the mechanical inertia response coefficient falls into the third interval, the output stability of the hybrid power system is marked as an inertia mismatch oscillation level.
8. The method for testing the output stability of a hybrid power system according to claim 3, characterized in that, The sampling moment when the instantaneous power change rate switches from a positive value to a negative value and the absolute value of the change rate is greater than a preset hysteresis threshold is defined as the power decrease inflection point.
9. The method for testing the output stability of a hybrid power system according to claim 5, characterized in that, The determination condition for identifying extreme points is that the instantaneous rate of change at the current moment is greater than the instantaneous rate of change at both the previous and next sampling moments.
10. A method for testing the output stability of a hybrid power system according to claim 6, characterized in that, The mechanical inertia reference value is calculated by multiplying the gear tooth ratio of the power coupling device by the square root of the shaft stiffness.