Description:ELECTRIC VEHICLE EFFICIENCY EVALUATION USING COAST DOWN TEST
FIELD OF INVENTION
[1] The present disclosure relates to diagnostic methods and tools for electric vehicles, and more particularly to a system for evaluating electric vehicle efficiency and health using coast down test data to predict range of the electric vehicle in real time.
BACKGROUND
[2] Electric vehicles (EVs) have gained significant popularity in recent years as a more environmentally friendly alternative to traditional internal combustion engine vehicles. As the adoption of EVs continues to grow, there is an increasing focus on improving their efficiency, performance, and overall user experience.
[3] One of the primary concerns for EV owners and potential buyers is range anxiety - the fear that the vehicle will run out of power before reaching its destination. This anxiety can be exacerbated by factors such as varying driving conditions, weather, and the natural degradation of battery performance over time. Accurate range estimation is therefore a crucial aspect of EV technology, as it directly impacts user confidence and the practical utility of these vehicles.
[4] Traditional methods of estimating EV range often rely on simplistic calculations based on the battery's state of charge and standardized driving cycles. However, these approaches may not accurately reflect real-world driving conditions or account for the specific characteristics of individual vehicles. As a result, users may experience discrepancies between the estimated and actual range, leading to uncertainty and potential inconvenience.
[5] Furthermore, the efficiency and health of an EV can be affected by various factors, including tire pressure, aerodynamics, and the condition of the powertrain components. Minor production abnormalities or wear and tear over time can impact the vehicle's overall resistance and energy consumption. Identifying and addressing these issues in a timely manner is essential for maintaining optimal performance and maximizing the vehicle's range.
[6] Existing diagnostic tools for EVs often focus on specific components or systems, such as battery health or motor performance. However, there is a need for comprehensive evaluation methods that can assess the overall efficiency and health of the vehicle in a practical and accessible manner. Such tools could provide valuable insights to both users and service technicians, enabling proactive maintenance and ensuring that EVs consistently deliver their expected performance.
[7] As the EV market continues to evolve, there is an ongoing need for innovative approaches to vehicle diagnostics, efficiency evaluation, and range prediction. Addressing these challenges can contribute to improved user satisfaction, reduced range anxiety, and ultimately, wider adoption of electric vehicle technology.
SUMMARY
[8] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
[9] According to an aspect of the present disclosure, a method for evaluating electric vehicle efficiency and health is provided. The method includes performing a coast down test on an electric vehicle by accelerating the vehicle to a predetermined speed and allowing it to freely decelerate. The method further includes collecting, via one or more sensors, data related to the vehicle's deceleration profile during the coast down test. The method also includes calculating, based on the collected data, coast down coefficients representing resistances acting on the vehicle. The method further includes determining, using the calculated coast down coefficients, an estimated range of the electric vehicle. The method also includes displaying the estimated range on a human-machine interface of the electric vehicle.
[10] According to other aspects of the present disclosure, the method may include one or more of the following features. The predetermined speed may be approximately 70 km/h. Collecting data related to the vehicle's deceleration profile may comprise measuring a stopping distance and time from for example from 60 kmph to 10 kmph. Calculating the coastdown coefficients may comprise determining coefficients A and C based on the deceleration profile and a gross weight of the vehicle. The method may further include measuring the gross weight of the vehicle using a load sensor on a suspension system of the vehicle. The method may also include comparing the estimated range to a predetermined threshold range. The method may further include generating a notification, if the estimated range is below the predetermined threshold range.
[11] According to another aspect of the present disclosure, a system for evaluating electric vehicle efficiency and health is provided. The system includes one or more sensors configured to collect data related to a vehicle's deceleration profile during a coast down test. The system also includes a processor and a memory storing instructions that, when executed by the processor, cause the system to calculate coast down coefficients based on the collected data, determine an estimated range of the electric vehicle using the calculated coast down coefficients, and display the estimated range on a human-machine interface of the electric vehicle.
[12] According to other aspects of the present disclosure, the system may include one or more of the following features. The coast down test may comprise accelerating the vehicle to approximately 70 kmph and allowing it to freely decelerate. The one or more sensors may include a GPS sensor configured to measure a stopping distance and time from predetermine speed range (for example 60 Kmph to 10 kmph during the coast down test. Calculating the coast down coefficients may comprise determining coefficients a and c based on the deceleration profile and a gross weight of the vehicle. The system may further include a load sensor on a suspension system of the vehicle configured to measure the gross weight of the vehicle. The instructions may further cause the system to compare the estimated range to a predetermined threshold range. The instructions may further cause the system to generate a notification, if the estimated range is below the predetermined threshold range.
[13] According to another aspect of the present disclosure, an electric vehicle is provided. The electric vehicle includes a propulsion system, one or more sensors configured to collect data related to the vehicle's deceleration profile during a coast down test, a human-machine interface, and a control unit. The control unit is configured to calculate coast down coefficients based on data collected by the one or more sensors during a coast down test, determine an estimated range of the electric vehicle using the calculated coast down coefficients, and display the estimated range on the human-machine interface.
[14] According to other aspects of the present disclosure, the electric vehicle may include one or more of the following features. The coast down test may comprise accelerating the vehicle to approximately 70 km/h and allowing it to freely decelerate. The one or more sensors may include a GPS sensor configured to measure a stopping distance and time for a predetermined speed range for example (from 60 kmph to 10 kmph) during the coast down test. Calculating the coast down coefficients may comprise determining coefficients a and c based on the deceleration profile and a gross weight of the vehicle. The electric vehicle may further include a load sensor on a suspension system of the vehicle configured to measure the gross weight of the vehicle. The control unit may be further configured to compare the estimated range to a predetermined threshold range and generate a notification, if the estimated range is below the predetermined threshold range.
[15] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.
BRIEF DESCRIPTION OF FIGURES
[16] Fig. 1 illustrates a method for evaluating electric vehicle efficiency and health using coast down test data, in accordance with the present invention.
DETAILED DESCRIPTION
[17] The following description sets forth exemplary aspects of the present disclosure. It should be recognized, however, that such description is not intended as a limitation on the scope of the present disclosure. Rather, the description also encompasses combinations and modifications to those exemplary aspects described herein.
[18] The present disclosure relates to a method 100 for evaluating electric vehicle efficiency and health using coast down test data. FIG. 1 illustrates a flowchart of the method 100, which may be implemented in an electric vehicle. The electric vehicle may include a propulsion system, one or more sensors, a processor, a memory, and a human-machine interface.
[19] In some cases, the method 100 begins with performing a vehicle coast down test (step 102). During the coast down test, the one or more sensors may collect data related to the vehicle's deceleration profile without applying regenerative brake or braking operation of the vehicle (step 104). The collected data may then be used to calculate coast down coefficients (step 106).
[20] Using the calculated coast down coefficients, the method 100 may determine an estimated range of the electric vehicle (step 108). The estimated range may be displayed on the human-machine interface of the electric vehicle (step 110).
[21] In some implementations, the method 100 may include comparing the estimated range to a predetermined threshold (step 112). If the estimated range falls below the predetermined threshold, a notification may be generated (step 114).
[22] The method 100 may provide a diagnostic tool for evaluating the efficiency and health of an electric vehicle using data collected during a simple coast down test. This approach may allow for quick assessment of vehicle performance without requiring complex or time-consuming procedures. In another embodiment, this assessment allows a quick check of the produced electric vehicle, before delivering production vehicle to customers.
[23] In some cases, the method 100 may begin with performing a coast down test on an electric vehicle, as shown in step 102 of FIG. 1. The coast down test may involve accelerating the electric vehicle to a predetermined speed and then allowing the vehicle to freely decelerate.
[24] The predetermined speed for the coast down test may vary depending on the specific implementation. In some cases, the predetermined speed may be approximately 70 kmph. Once the electric vehicle reaches the predetermined speed, the driver or an automated system may release the accelerator pedal/throttle, allowing the vehicle to coast without applying any additional propulsion power.
[25] During the coast down test, the electric vehicle may be allowed to decelerate naturally due to various resistances acting on the vehicle, such as aerodynamic drag, rolling resistance, and other mechanical losses. The vehicle may continue to decelerate until it comes to a complete stop or reaches a lower predetermined speed (for example decelerating from 60 kmph to 30 kmph).
[26] It is important to note that during the coast down test, no regenerative braking or mechanical braking may be applied. This ensures that the deceleration profile obtained during the test accurately reflects the natural resistances acting on the electric vehicle.
[27] The coast down test may be performed on a flat, straight road with minimal wind interference to obtain consistent and reliable results. In some cases, multiple coast down tests may be conducted and averaged to improve the accuracy of the data collected.
[28] In some cases, the method 100 may involve collecting deceleration data from the vehicle during the coast down test, as represented by step 104 in FIG. 1. The deceleration data may be collected using one or more sensors configured to measure various parameters related to the vehicle's deceleration profile.
[29] The one or more sensors may include a GPS sensor configured to measure the vehicle's position and speed over time during the coast down test. In some implementations, the GPS sensor may be used to measure the stopping distance and time over a predetermined speed range during the deceleration process. For example, the GPS sensor may record the distance traveled and time elapsed as the vehicle decelerates from 60 kmph to 10 kmph.
[30] In addition to the GPS sensor, other sensors may be employed to collect relevant data during the coast down test. These sensors may include accelerometers to measure the vehicle's deceleration rate, wheel speed sensors to monitor the rotation of the wheels, and inclinometers to detect any changes in road grade that may affect the deceleration profile.
[31] The data collection process may be initiated automatically when the coast down test begins and may continue until the vehicle comes to a complete stop or reaches a predetermined lower speed threshold. It is important to note that the data collection occurs before any regenerative braking or mechanical braking operation is applied to the vehicle. This ensures that the collected data accurately represents the natural deceleration of the vehicle due to various resistances such as aerodynamic drag and rolling resistance.
[32] In some cases, the collected data may include time-stamped measurements of the vehicle's speed, position, and acceleration at regular intervals throughout the coast down test. This raw data may be stored in the vehicle's memory for subsequent analysis and calculation of coast down coefficients.
[33] The method 100 may also involve pre-processing the collected data to remove any outliers or noise that may affect the accuracy of subsequent calculations. This pre-processing step may include applying filtering algorithms or averaging techniques to smooth the deceleration profile data.
[34] In some cases, the method 100 may involve calculating coast down coefficients based on the collected deceleration data, as shown in step 106 of FIG. 1. The coast down coefficients may represent resistances acting on the electric vehicle during the coast down test.
[35] The calculation of coast down coefficients may comprise determining coefficients A and C based on the deceleration profile and a gross weight of the electric vehicle. Coefficient a may represent the constant resistance, while coefficient c may represent the aerodynamic drag coefficient.
[36] In some implementations, the gross weight of the electric vehicle may be measured using a load sensor on a suspension system of the electric vehicle. The load sensor may provide real-time weight data to account for variations in vehicle load during different test conditions.
[37] The mathematical model may be expressed as to predict the range of the electric vehicle is

Where:
R = Range of the electric vehicle
A and C are coast down coefficients of the electric vehicle
X0, X1, X2, X3, X4, X5 are coefficients calculated using regression.

[38] Using the deceleration profile data and the measured gross weight, the method 100 may employ regression analysis or other curve-fitting techniques to determine the values of coefficients A and C that best fit the observed deceleration behavior.
[39] In some cases, the calculation of coast down coefficients may be performed by a processor executing instructions stored in a memory of the electric vehicle. The processor may apply numerical methods to solve for the coefficients A and C based on the collected deceleration data and vehicle weight.
[40] Once the coast down coefficients A and C are determined, the method 100 may use these coefficients to estimate the range of the electric vehicle. The range estimation may be based on a specific mathematical equation that incorporates the A and C coefficients.
[41] The calculated coast down coefficients A and C, may provide valuable information about the resistances acting on the electric vehicle, allowing for a more accurate estimation of vehicle efficiency and range. By using real-time weight measurements and deceleration profile data, the method 100 may account for variations in vehicle load and environmental conditions, potentially improving the accuracy of the range estimation.
[42] In some cases, the method 100 may involve determining an estimated range of the electric vehicle using the calculated coast down coefficients, as shown in step 108 of FIG. 1. The coast down coefficients, specifically coefficients A and C, may be used to estimate the vehicle's range based on the resistances acting on the vehicle during the coast down test.
[43] The processor of the electric vehicle may execute instructions stored in the memory to determine the estimated range. In some implementations, the processor may apply a mathematical model that incorporates the coast down coefficients along with other relevant parameters to calculate the estimated range by using the mathematical model as follows,

Where:
R = Range of the electric vehicle
A and C are coast down coefficients of the electric vehicle
X0, X1, X2, X3, X4, X5 are coefficients calculated using regression
[44] The control unit of the electric vehicle may be configured to perform the range estimation calculations in real-time or at predetermined intervals. In some implementations, the control unit may update the estimated range continuously as the vehicle operates, taking into account changes in battery state of charge, ambient conditions, and other relevant factors.
[45] The estimated range determined using the coast down coefficients may provide a more accurate representation of the vehicle's actual range compared to estimates based solely on battery capacity and average energy consumption. By accounting for the specific resistances acting on the vehicle, as captured by the coast down coefficients, the range estimation may better reflect the vehicle's current efficiency and performance characteristics.
[46] In some cases, method 100 may involve displaying the estimated range on a human-machine interface of the electric vehicle, as shown in step 110 of FIG. 1. The human-machine interface may be a display screen located on the vehicle's dashboard or instrument cluster.
[47] The processor of the electric vehicle may execute instructions stored in the memory to control the display of the estimated range on the human-machine interface. The control unit of the electric vehicle may be configured to format and transmit the estimated range data to the human-machine interface for display.
[48] In some implementations, the estimated range may be displayed as a numerical value, typically in units of distance such as kilometers or miles. The display may also include a graphical representation of the estimated range, such as a battery icon with a fill level corresponding to the remaining range.
[49] The location of the estimated range display on the human-machine interface may vary depending on the specific vehicle design. In some cases, the estimated range may be prominently displayed in the center of the instrument cluster, allowing for easy visibility by the driver. In other implementations, the estimated range may be displayed in a dedicated section of the dashboard display or integrated into a larger information panel.
[50] The control unit may be configured to update the displayed estimated range in real-time or at regular intervals. This may allow the driver to monitor changes in the estimated range as the vehicle operates under different conditions or as the battery charge level changes.
[51] In some cases, the human-machine interface may provide additional context for the displayed estimated range. This may include color-coding to indicate different range levels (e.g., green for sufficient range, yellow for moderate range, red for low range) or displaying the estimated range alongside other relevant information such as current speed, battery state of charge, or energy consumption rate.
[52] The display of the estimated range on the human-machine interface may provide the driver with easily accessible information about the vehicle's current efficiency and expected driving range. This information may help drivers make informed decisions about their travel plans and charging needs.
[53] In some cases, method 100 may involve comparing the estimated range to a predetermined threshold range, as represented by step 112 in FIG. 1. The processor of the electric vehicle may execute instructions stored in the memory to perform this comparison.
[54] The predetermined threshold range may be a value or range of values that represent the minimum acceptable range for the electric vehicle. This threshold may be determined based on various factors, such as:
[55] 1. The vehicle's certified range
[56] 2. A percentage of the certified range (e.g., 90% of the certified range)
[57] 3. A fixed distance value (e.g., 200 km)
[58] 4. A dynamic value based on historical performance data
[59] In some implementations, the control unit of the electric vehicle may be configured to compare the estimated range calculated in step 108 to the predetermined threshold range. The comparison may involve a simple numerical comparison between the estimated range and the threshold value.
[60] The significance of this comparison lies in its ability to identify potential issues with the vehicle's efficiency or performance. If the estimated range falls below the predetermined threshold range, method 100 may proceed to step 114, where a notification may be generated.
[61] The processor may be programmed to perform this comparison automatically after each coast down test or at regular intervals during vehicle operation. In some cases, the comparison may be triggered by specific events, such as:
[62] 1. After a certain number of kilometers driven
[63] 2. When the battery state of charge reaches a certain level
[64] 3. At scheduled maintenance intervals
[65] The control unit may store the results of these comparisons in the memory, allowing for tracking of the vehicle's range performance over time. This historical data may be used to identify trends or patterns in the vehicle's efficiency and may inform maintenance decisions or adjustments to the predetermined threshold range.
[66] In some implementations, the human-machine interface may display the results of this comparison to the driver. For example, the interface may show both the estimated range and the threshold range, allowing the driver to easily understand the vehicle's current performance relative to expectations.
[67] The comparison of the estimated range to the predetermined threshold range may serve as a diagnostic tool, helping to identify potential issues with the vehicle's efficiency before they significantly impact the driver's experience. By regularly performing this comparison, the method 100 may contribute to maintaining the vehicle's performance and ensuring customer satisfaction.
[68] In some cases, the method 100 may involve generating a notification if the estimated range is below a predetermined threshold range, as shown in step 114 of FIG. 1. The control unit of the electric vehicle may be configured to generate this notification based on the comparison performed in step 112.
[69] The notification may be generated for at least one of the drivers of the electric vehicle or a maintenance person. In some implementations, the notification may be displayed on the human-machine interface of the electric vehicle, alerting the driver to potential efficiency issues. Additionally, the notification may be transmitted to a maintenance system or personnel via a wireless communication system.
[70] The control unit may be programmed to include specific information in the notification, such as:
[71] 1. The current estimated range
[72] 2. The predetermined threshold range
[73] 3. The difference between the estimated range and the threshold
[74] 4. Potential causes for the reduced range
[75] In some cases, the notification may include diagnostic information based on the calculated coast down coefficients. For example, if the coefficient a is higher than a predetermined threshold, the notification may indicate potential issues related to static resistance, such as:
[76] 1. Dust boot clogging
[77] 2. Insufficient chain lubrication
[78] 3. Increased tire rolling resistance
[79] 4. Chain or belt misalignment
[80] 5. Tire wear
[81] 6. Incorrect tire pressure
[82] The control unit may access stored comparison data from the vehicle control unit (VCU) to evaluate if the actual range is consistently less than the calculated range. This historical data may be included in the notification to provide context for the current range estimation.
[83] In some implementations, the notification process may involve additional diagnostic steps. The control unit may be configured to initiate a check of electrical connections for unintended heating if the efficiency has deteriorated. Additionally, the control unit may run a cloud check to assess individual system health and driving patterns, which may help identify the root cause of the reduced range.
[84] The notification may serve multiple purposes:
[85] 1. Alert the driver or maintenance personnel to potential efficiency issues
[86] 2. Provide guidance for targeted maintenance or repairs
[87] 3. Help prevent unexpected range limitations during vehicle operation
[88] 4. Contribute to overall vehicle health monitoring and preventive maintenance
[89] By generating notifications when the estimated range falls below the predetermined threshold, the method 100 may help ensure that electric vehicles maintain their expected performance and efficiency over time. This proactive approach to vehicle diagnostics may contribute to improved customer satisfaction and reduced maintenance costs.
[90] A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.
, C , Claims:I/WE CLAIM
1. A method for evaluating electric vehicle efficiency and health, comprising:
performing a coast down test on an electric vehicle by accelerating the vehicle to a predetermined speed and allowing it to freely decelerate;
collecting, via one or more sensors, data related to the vehicle's deceleration profile during the coast down test without applying regenerative brake or braking operation of the vehicle;
calculating, based on the collected data, coast down coefficients representing resistances acting on the vehicle;
determining, using the calculated coast down coefficients, an estimated range of the electric vehicle; and
displaying the estimated range on a human-machine interface of the electric vehicle.
2. The method of claim 1, wherein collecting data related to the vehicle's deceleration profile comprises measuring a stopping distance and time over a predetermined speed range during deceleration.
3. The method of claim 1, wherein calculating the coast down coefficients comprises determining coefficients A and C based on the deceleration profile and a gross weight of the vehicle.
4. The method of claim 3, further comprising measuring the gross weight of the vehicle using a load sensor on a suspension system of the vehicle.
5. The method of claim 1, further comprising comparing the estimated range to a predetermined threshold range.
6. The method of claim 5, further comprising generating a notification to at least one of a driver of the vehicle or a maintenance person, if the estimated range is below the predetermined threshold range.
7. The method of claim 6, wherein the notification includes diagnostic information based on the calculated coast down coefficients, and wherein if coefficient a is higher than a predetermined threshold, the notification indicates one or more potential issues related to static resistance, including dust boot clogging, insufficient chain lubrication, increased tire rolling resistance, chain or belt misalignment, tire wear, or incorrect tire pressure.
8. A system for evaluating electric vehicle efficiency and health, comprising:
one or more sensors configured to collect data related to a vehicle's deceleration profile during a coast down test without applying regenerative brake or braking operation of the vehicle;
a processor; and
a memory storing instructions that, when executed by the processor, cause the system to:
calculate coast down coefficients based on the collected data;
determine an estimated range of the electric vehicle using the calculated coast down coefficients; and
display the estimated range on a human-machine interface of the electric vehicle.
9. The system of claim 7, wherein the coast down test comprises accelerating the vehicle to a predetermined speed range and allowing it to freely decelerate.
10. The system of claim 7, wherein the one or more sensors include a GPS sensor configured to measure a stopping distance and time over a predetermined speed range during the coast down test.
11. The system of claim 7, wherein calculating the coast down coefficients comprises determining coefficients a and c based on the deceleration profile and a gross weight of the vehicle.
12. The system of claim 10, further comprising a load sensor on a suspension system of the vehicle configured to measure the gross weight of the vehicle.
13. The system of claim 7, wherein the instructions further cause the system to compare the estimated range to a predetermined threshold range.
14. The system of claim 12, wherein the instructions further cause the system to generate a notification if the estimated range is below the predetermined threshold range.
15. An electric vehicle, comprising:
a propulsion system;
one or more sensors configured to collect data related to the vehicle's deceleration profile during a coast down test without applying regenerative brake or braking operation of the vehicle;
a human-machine interface; and
a control unit configured to:
calculate coast down coefficients based on data collected by the one or more sensors during a coast down test;
determine an estimated range of the electric vehicle using the calculated coast down coefficients; and
display the estimated range on the human-machine interface.
16. The electric vehicle of claim 14, wherein the coast down test comprises accelerating the vehicle to approximately 70 km/h and allowing it to freely decelerate.
17. The electric vehicle of claim 14, wherein the one or more sensors include a GPS sensor configured to measure a stopping distance and time over a predetermined speed range during the coast down test.
18. The electric vehicle of claim 14, wherein calculating the coast down coefficients comprises determining coefficients a and c based on the deceleration profile and a gross weight of the vehicle.
19. The electric vehicle of claim 17, further comprising a load sensor on a suspension system of the vehicle configured to measure the gross weight of the vehicle.
20. The electric vehicle of claim 18, wherein the control unit is further configured to:
compare the estimated range to a predetermined threshold range; and
generate a notification if the estimated range is below the predetermined threshold range.