Description:TECHNICAL FIELD
[0001] The present disclosure relates generally to battery management systems for battery packs in electric vehicles. In particular, the present disclosure relates to a simple, efficient, cost-effective energy management system and a method for a heavy-duty electric vehicle to prevent over-discharging/charging of a battery pack.

BACKGROUND
[0002] At present, demand for electric vehicles (EVs), particularly heavy-duty electric vehicles, has surged due to an increasing need for sustainable and environmentally friendly transportation solutions. However, the transition from conventional internal combustion (IC) engines to electric propulsion systems presents several challenges, particularly in terms of energy storage and management. Heavy-duty electric vehicles require sophisticated energy storage systems capable of delivering high power and energy density instantaneously to meet the demands of various operational conditions, such as acceleration, braking, and regenerative energy capture.
[0003] Conventional energy storage systems in heavy-duty electric vehicles primarily rely on batteries, which, while effective in storing energy, face limitations in handling transient power demands and regenerative braking energy efficiently. Batteries are prone to rapid degradation when subjected to high C-rates, which are common in heavy-duty applications due to frequent acceleration and deceleration. The said degradation not only reduces the lifespan of the battery but also affects the overall performance and reliability of the vehicle. Additionally, batteries alone may not efficiently capture and utilize regenerative braking energy, leading to energy losses and reduced vehicle efficiency.
[0004] Thus there is a need for mitigating the challenges associated with the conventional battery management systems by providing a combinational energy storage device that is capable of integrating both batteries and supercapacitors through an improved energy management system to handle transient currents effectively, thereby improving the overall performance of heavy-duty electric vehicles but also reduces the aging effects on battery packs, leading to a more sustainable and cost-effective solution for electric transportation.

OBJECTIVES OF THE PRESENT DISCLOSURE
[0005] A general objective of the present disclosure is to mitigate the challenges associated with battery management systems for battery packs in electric vehicles by providing a simple, efficient, cost-effective, and improved energy management system and a method for a heavy-duty electric vehicle to prevent over-discharging/charging of a battery pack.
[0006] An objective of the present disclosure is to regulate the electricity discharged from the battery pack to ensure a steady flow of electricity is being drawn from the battery pack.
[0007] An objective of the present disclosure is to regulate regenerated electricity before being received into the battery pack to ensure the battery pack is charged by a steady flow of regenerated electricity.
[0008] An objective of the present disclosure is to maintain a state of charge (SoC) of the battery pack and the supercapacitor of the heavy-duty electric vehicle within predefined permissible limits for them to efficiently meet transient power demands of the heavy-duty electric vehicle, thereby optimizing the performance and lifespan of the battery pack of the heavy-duty electric vehicle.

SUMMARY
[0009] Aspects of the present disclosure pertain to the field of battery management systems for battery packs in electric vehicles. In particular, the present disclosure relates to a simple, compact, efficient, and improved energy management system and a method for a heavy-duty electric vehicle to prevent over-discharging/charging of a battery pack.
[0010] According to an aspect, an energy management system for a heavy-duty electric vehicle is disclosed. The energy management system includes a battery pack, a supercapacitor, and a controller. The battery pack and the supercapacitor are assembled within the heavy-duty electric vehicle. The controller includes a first low pass filter, a second low pass filter, a first learning module, and a second leaning module.
[0011] The controller is in communication with the battery pack and the supercapacitor. The controller is configured to regulate a first state of charge (SoC) of the battery pack to a first predefined level using the first learning module and the first low pass filter. The controller ensures a steady discharge of electricity from the battery pack to partially meet the torque demands of heavy-duty electric vehicle. Additionally, the controller receives a filtered regulated supply of regenerative electricity from the heavy-duty electric vehicle using the second low pass filter.
[0012] The controller regulates a second state of charge (SoC) of the supercapacitor to a second predefined level using the second learning module. The controller enables the supercapacitor to supply additional electricity required to compensate actual torque demand of the heavy-duty electric vehicle. The suppled electricity is in addition to the steady flow of electricity received from the battery pack.
[0013] The system maintains the first and second SoCs within their respective first and second predefined levels using the first learning module. The system prevents over-discharging or over-charging of the battery pack and ensuring optimal performance of the battery pack of the heavy-duty electric vehicle.
[0014] In an embodiment, the first low pass filter may be configured to provide a low-frequency reference power during discharging.
[0015] In an embodiment, the second low pass filter may be configured to provide a low-frequency reference power during regeneration.
[0016] In an embodiment, the first learning module may be a rule-based control module.
[0017] In an embodiment, the second learning module may be a power map module.
[0018] In an embodiment, the first predefined limit of the first SoC may be selected between a range of 20% and 90%. The second predefined limit of the second SoC may be selected between a range of 20% and 95%.
[0019] In an embodiment, the system may include a bi-directional converter. The bi-directional converter may be communicably coupled to the battery pack, the supercapacitor, and the controller. The bi-directional converter may interface the supercapacitor with a Direct Current (DC) bus of the heavy-duty electric vehicle. The Direct Current (DC) bus may be operated in a boost mode while discharging electricity and a buck mode while charging.
[0020] In an embodiment, the system may be configured to reduce the root mean square (RMS) value of the discharging and charging of the battery pack. The reduction of RMS value may reduce heat generated while discharging and charging of the battery pack.
[0021] According to an aspect, a method implemented by a system for managing energy in a heavy-duty electric vehicle is disclosed. The method beings with an initial step of predicting the actual electricity required using a controller to meet a torque demand of the heavy-duty electric vehicle.
[0022] The method includes a step of drawing steady electricity from a battery pack using a first low pass filter implemented by the controller to partially meet the torque demand of the heavy-duty electric vehicle and another step of additionally drawing remaining electricity from a supercapacitor using a bi-directional converter for compensating the steady electricity discharged from the battery pack.
[0023] The method includes a final step of maintaining a first state of charge (SoC) of the battery pack within a first predefined level and a second SoC of the supercapacitor within a second predefined level using a first learning module implemented by the controller to prevent over-discharging or over-charging of the battery pack.
[0024] In an embodiment, the method may include another step of filtering regenerated electricity for ensuring steady flow of the regenerated electricity from the heavy-duty electric vehicle into the battery pack.
[0025] Various objects, features, aspects, and advantages of the subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.
BRIEF DESCRIPTION OF DRAWINGS
[0026] The accompanying drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure. The diagrams are for illustration only, which thus is not a limitation of the present disclosure.
[0027] FIG. 1 is an exemplary block diagram illustrating an energy management system for a heavy-duty electric vehicle, in accordance with embodiments of the present disclosure.
[0028] FIG. 2 is an exemplary flow diagram describing a method implemented by the proposed energy management system for the heavy-duty electric vehicle, in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION
[0029] For the purpose of promoting an understanding of the principles of the present disclosure, reference will now be made to the various embodiments and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the present disclosure is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the present disclosure as illustrated therein being contemplated as would normally occur to one skilled in the art to which the present disclosure relates.
[0030] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the present disclosure and are not intended to be restrictive thereof.
[0031] Whether or not a certain feature or element was limited to being used only once, it may still be referred to as “one or more features” or “one or more elements” or “at least one feature” or “at least one element.” Furthermore, the use of the terms “one or more” or “at least one” feature or element do not preclude there being none of that feature or element, unless otherwise specified by limiting language including, but not limited to, “there needs to be one or more…” or “one or more elements is required.
[0032] Reference is made herein to some “embodiments.” It should be understood that an embodiment is an example of a possible implementation of any features and/or elements of the present disclosure. Some embodiments have been described for the purpose of explaining one or more of the potential ways in which the specific features and/or elements of the proposed disclosure fulfil the requirements of uniqueness, utility, and non-obviousness.
[0033] Use of the phrases and/or terms including, but not limited to, “a first embodiment,” “a further embodiment,” “an alternate embodiment,” “one embodiment,” “an embodiment,” “multiple embodiments,” “some embodiments,” “other embodiments,” “further embodiment”, “furthermore embodiment”, “additional embodiment” or other variants thereof do not necessarily refer to the same embodiments. Unless otherwise specified, one or more particular features and/or elements described in connection with one or more embodiments may be found in one embodiment, or may be found in more than one embodiment, or may be found in all embodiments, or may be found in no embodiments. Although one or more features and/or elements may be described herein in the context of only a single embodiment, or in the context of more than one embodiment, or in the context of all embodiments, the features and/or elements may instead be provided separately or in any appropriate combination or not at all. Conversely, any features and/or elements described in the context of separate embodiments may alternatively be realized as existing together in the context of a single embodiment.
[0034] Any particular and all details set forth herein are used in the context of some embodiments and therefore should not necessarily be taken as limiting factors to the proposed disclosure. The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by “comprises... a” does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.
[0035] Embodiments explained herein relate to a simple, compact, efficient, and improved energy management system and a method for a heavy-duty electric vehicle to prevent over-discharging/charging of a battery pack.
[0036] According to an aspect, the disclosed energy management system is designed for a heavy-duty electric vehicle which while moving has transient power demands, especially during acceleration and braking. The transient power demands when directly drawn from the heavy-duty electric vehicle’s battery pack increase the load thereby increasing C-rate fluctuations of said battery pack and reducing the lifespan of the battery pack. The disclosed energy management system includes a battery pack, a supercapacitor, and a controller.
[0037] The controller in communication with the battery pack and the supercapacitor regulates a first state of charge (SoC) of the battery pack to a first predefined level using the first learning module and the first low pass filter. The controller may enable steady discharge of electricity from the battery pack to partially meet the torque demands of heavy-duty electric vehicle.
[0038] Additionally, the controller regulates a second SoC of the supercapacitor to a second predefined level using the second learning module for supplying additional electricity required from the supercapacitor. The supplied additional electricity may compensate an actual torque demand of the heavy-duty electric vehicle in addition to the steady flow of electricity received from the battery pack for preventing over-discharging or over-charging of the battery pack.
[0039] Further, the system ensures optimal performance of the battery pack with reduced C-rate upon being tested and validated under different drive cycles and different SoC conditions with conventional battery management systems that use a single low pass filter.
[0040] Various embodiments of the present disclosure will be explained in detail with reference to FIGs. 1 and 2.
[0041] Referring to FIG. 1, the proposed energy management system (hereinafter referred to as “energy management system 100” or simply “system 100”) for a heavy-duty electric vehicle includes a battery pack 102 of the heavy-duty electric vehicle, a supercapacitor 104 assembled within the heavy-duty electric vehicle, and a controller 106 in communication with the battery pack 102 and the supercapacitor 104. The controller 106 partially and steadily draws electricity from the battery pack 102 while supplementing the remaining required electricity from the supercapacitor 104 to ensure that the total supply of electricity matches the actual torque demand of the heavy-duty electric vehicle. The system 100 maintains a stable load on the battery pack 102 while the supercapacitor 104 compensates for instantaneous electricity demand spikes, preventing over-discharging or over-charging of the battery pack 102 and ensuring optimal performance of the battery pack 102 of the heavy-duty electric vehicle. The supercapacitor 104 may partially handle transient power demands in addition to the battery pack 102 during acceleration and braking of the heavy-duty electric vehicle, thereby reducing the C-rate fluctuations of the battery pack 102.
[0042] In an embodiment, the controller 106 includes a first low pass filter 106A, a second low pass filter 106B, a first learning module 106C that may correspond to a rule-based control module, and a second learning module 106D that may correspond to a power map module. The first low pass filter 106A may provide a low-frequency reference power during discharging of the battery pack 102. The second low pass filter 106B may provide a low-frequency reference power during regeneration of electricity from the heavy-duty electric vehicle from heat generated while braking. The second learning module 106D may generate a balancing reference power to adjust the second SoC of the supercapacitor 104, generating a large recharging power reference when the second SoC is low and a large discharging power reference when the second SoC is high.
[0043] The controller 106 may regulate a first state of charge (SoC) of the battery pack 102 to a first predefined level that may be selected between a range of 20% and 90% using the first learning module 106C and the first low pass filter 106A. The controller 106 may ensure a steady discharge of electricity from the battery pack 102 to partially meet the torque demands of heavy-duty electric vehicle.
[0044] Additionally, the controller 106 may regulate a second state of charge (SoC) of the supercapacitor 104 to a second predefined level that may be selected between a range of 20% and 95% using the second learning module 106D. The controller 106 may enable the supercapacitor 104 to supply additional electricity required to compensate for the actual torque demand of the heavy-duty electric vehicle in addition to the steady flow of electricity received from the battery pack 102. The controller 106 may regulate a second state of charge (SoC) of the supercapacitor 104 to a second predefined level that may be selected between a range of 20% and 95% using a second learning module 106D for enabling the supercapacitor 104 to supply additional electricity required to compensate for the actual torque demand of the heavy-duty electric vehicle in addition to the steady flow of electricity received from the battery pack 102.
[0045] Further, the controller 106 may receive a filtered regulated supply of regenerative electricity from the heavy-duty electric vehicle using the second low pass filter 106B. The regenerative electricity from the heavy-duty electric vehicle may be generated during the braking phase of the moving heavy-duty electric vehicle.
[0046] In an embodiment, the system 100 may include a bi-directional converter 108. The bi-directional converter 108 may be in communication with the battery pack 102, the supercapacitor 104, and the controller 106. The bi-directional converter 108 may interface the supercapacitor 104 with a Direct Current (DC) bus of the heavy-duty electric vehicle for being operated in a boost mode while discharging electricity and a buck mode while charging.
[0047] In an embodiment, the system 100 may reduce the root mean square (RMS) value of the discharging and charging of the battery pack 102. The reduction of the RMS value may reduce the heat generated while discharging and charging of the battery pack 102. The system 100 maintains the first and second SoCs within their respective first and second predefined levels using the first learning module 106C, thereby preventing over-discharging or over-charging of the battery pack 102 and ensuring optimal performance of the battery pack 102 of the heavy-duty electric vehicle.
[0048] Referring to FIG.2, a method (hereinafter referred to as “method 200”) implemented by a system 100 for managing energy in a heavy-duty electric vehicle includes a step 202 of predicting an actual electricity required to meet a torque demand of the heavy-duty electric vehicle using a controller 106.
[0049] Additionally, the method 200 includes another step 204 of drawing steady electricity from a battery pack 102 using a first low pass filter 106A implemented by the controller 106 to partially meet the torque demand of the heavy-duty electric vehicle. The controller 106 may regulate a first state of charge (SoC) of the battery pack 102 to a first predefined level that may be selected between a range of 20% and 90% using a first learning module 106C and the first low pass filter 106A for ensuring a steady discharge of electricity from the battery pack 102 to partially meet the torque demands of the heavy-duty electric vehicle. The first low pass filter 106A may provide a low-frequency reference power during discharging of the battery pack 102.
[0050] In furtherance to the above step 204, the method 200 may additionally draw remaining electricity from a supercapacitor 104 in a step 206 for compensating steady electricity discharged from the battery pack 102 such that the actual electricity required to meet torque demand is received by a bidirectional converter 108. The bidirectional converter 108 upon receiving the combined electricity that meets the actual torque demand of the heavy-duty electric vehicle, from the battery pack 102 and the supercapacitor 104 may supply the said combined electricity to a DC bus of the heavy-duty electric vehicle. The DC bus may further supply the received combined electricity to an electric motor of the heavy-duty electric vehicle.
[0051] The method 200 concludes with a final step 208 of maintaining the first state of charge (SoC) of the battery pack 102 within the first predefined level and the second SoC of the supercapacitor 104 within the second predefined level to prevent over-discharging or over-charging of the battery pack 102 for ensuring optimal performance of the battery pack 102 of the heavy-duty electric vehicle.
[0052] Furthermore, the method 200 may further include another step of filtering for enabling a steady flow of regenerated electricity from the heavy-duty electric vehicle into the battery pack 102 using a second low pass filter 106B implemented by the controller 106. The second low pass filter 106B may provide a low-frequency reference power during regeneration of electricity from the heavy-duty electric vehicle due to heat generated during braking phase of the heavy-duty electric vehicle.
[0053] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions, or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0054] The present disclosure provides a simple, efficient, cost-effective, and improved energy management system and a method for a heavy-duty electric vehicle to prevent over-discharging/charging of a battery pack.
[0055] The present disclosure increases lifespan of the battery pack of the heavy-duty electric vehicles by reducing root mean square (RMS) value while charging and discharging of the battery pack, minimizing heat generation, and preventing high C-rate fluctuations that accelerate aging of the battery pack.
[0056] The present disclosure improves overall energy efficiency of the heavy-duty electric vehicle by optimizing the distribution and utilization of electricity between the battery and supercapacitor, thereby reducing energy losses and maximizing the traveling range of the heavy-duty electric vehicle.
[0057] The present disclosure manages transient power demands during acceleration and braking of the heavy-duty electric vehicle, ensuring that the supercapacitor absorbs and supplies quick bursts of energy, thereby reducing stress on the battery pack.
[0058] The present disclosure maximizes capture and utilization of regenerative electricity generated during the braking phase of the heavy-duty electric vehicle, ensuring that regenerated electricity is efficiently stored within the battery pack and reused.
, Claims:1. An energy management system for a heavy-duty electric vehicle, the system (100) comprising:
a battery pack (102) of the heavy-duty electric vehicle;
a supercapacitor (104) assembled within the heavy-duty electric vehicle;
a controller (106) comprises a first low pass filter (106A), a second low pass filter (106B), a first learning module (106C) (a rule-based control module), and a second leaning module (106D) (power map module), and is in communication with the battery pack (102) and the supercapacitor (104), the controller (106) is configured to:
regulate a first state of charge (SoC) of the battery pack (102) to a first predefined level using the first learning module (106C) (rule-based control module) and the first low pass filter (106A), to ensure a steady discharge of electricity from the battery pack (102) to partially meet the torque demands of heavy-duty electric vehicle, and receive a filtered regulated supply of regenerative electricity from the heavy-duty electric vehicle using the second low pass filter (106B); and
regulate a second state of charge (SoC) of the supercapacitor (104) to a second predefined level using the second learning module (106D) (power map module), enabling the supercapacitor (104) to supply additional electricity required to compensate actual torque demand of the heavy-duty electric vehicle in addition to the steady flow of electricity received from the battery pack (102),
wherein the system (100) maintains the first and second SoCs within their respective first and second predefined levels using the first learning module (106C), thereby preventing over-discharging or over-charging of the battery pack (102) and ensuring optimal performance of the battery pack (102) of the heavy-duty electric vehicle.
2. The system (100) as claimed in claim 1, wherein the first low pass filter (106A) is configured to provide a low-frequency reference power during discharging.
3. The system (100) as claimed in claim 1, wherein the second low pass filter (106B) is configured to provide a low-frequency reference power during regeneration.
4. The system (100) as claimed in claim 1, wherein the first learning module (106C) is a rule-based control module.
5. The system (100) as claimed in claim 1, wherein the second learning module (106D) is a power map module.
6. The system (100) as claimed in claim 1, wherein the first predefined limit of the first SoC is selected between a range of 20% and 90%, wherein the second predefined limit of the second SoC is selected between a range of 20% and 95%.
7. The system (100) as claimed in claim 1, wherein the system (100) comprises a bi-directional converter (108) communicably coupled to the battery pack (102), the supercapacitor (104), and the controller (106), wherein the bi-directional converter (108) interfaces the supercapacitor (104) with a Direct Current (DC) bus of the heavy-duty electric vehicle for being operated in a boost mode while discharging electricity and a buck mode while charging.
8. The system (100) as claimed in claim 1, wherein the system (100) is configured to reduce the root mean square (RMS) value of the discharging and charging of the battery pack (102), wherein the reduction in RMS valve reduces heat generated while discharging and charging of the battery pack (102).
9. A method (200) implemented by a system (100) for managing energy in a heavy-duty electric vehicle, comprising:
predicting (202), using a controller (106) the actual electricity required to meet a torque demand of the heavy-duty electric vehicle;
drawing (204), using a first low pass filter (106A) implemented by the controller (106), steady electricity from a battery pack (102) to partially meet the torque demand of the heavy-duty electric vehicle;
additionally drawing (206), using a bi-directional converter (108), remaining electricity from a supercapacitor (104) for compensating the steady electricity discharged from the battery pack (102);
maintaining (208), using a first learning module (106C) implemented by the controller (106), a first state of charge (SoC) of the battery pack (102) within a first predefined level and a second SoC of the supercapacitor (104) within a second predefined level to prevent over-discharging or over-charging of the battery pack (102).
10. The method (200) as claimed in claim 9, wherein the method (200) includes a step of filtering, using the second low pass filter (106B) implemented by the controller (106), regenerated electricity generated from the heavy-duty electric vehicle to ensure a steady flow of the regenerated electricity is received by the battery pack (102) while charging.