System and method for vehicle load management

Abstract

A method for analyzing and managing a vehicle load carried by a vehicle having a fluid suspension system, the method comprising: sampling a fluid pressure corresponding to a set of fluid springs of the fluid suspension system at a manifold, wherein the set of fluid springs supports the vehicle load; determining an existing stiffness distribution, the existing stiffness distribution including a stiffness value associated with each fluid spring in the set of fluid springs; determining a fore-aft related data set during vehicle operation; determining a desired stiffness distribution based on the fore-aft related data set; and automatically controlling the set of fluid springs at a plurality of drive points based on the desired stiffness distribution, wherein controlling the set of fluid springs includes setting a stiffness value for the fluid spring associated with each drive point.

Description

[0001] This application is a divisional application of "System and method for vehicle load management" with an international application date of January 4, 2018 and Chinese application number "201880015365.8" (international application number "PCT / US2018 / 012393"). This application claims the benefit of U.S. Provisional Application No. 62 / 442,119 filed on January 4, 2017 and the benefit of U.S. Provisional Application No. 62 / 564,953 filed on September 28, 2017, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present invention relates generally to the field of vehicle load management and, more particularly, to a new and useful system and method for analyzing and controlling vehicle pressure systems in this field. Background Art

[0003] Typically, adverse outcomes for vehicles carrying cargo are caused by improper arrangement and / or distribution of the load within the vehicle, the consequences of which may include: collisions (e.g., uncontrolled jackknifing), improper handling and operation, poor fuel efficiency and / or time efficiency, and other undesirable vehicle operating conditions.

[0004] Therefore, there is a need for a new and useful system and / or method in the field of vehicle load management to solve the above problems and other related load management problems. The present invention provides such a new and useful system and method. Summary of the invention

[0005] A method for analyzing and managing vehicle load according to the present invention, the vehicle having a fluid suspension system for supporting the vehicle load, the method comprising:

[0006] -determine a set of loading criteria;

[0007] - sampling a set of fluid pressures corresponding to a set of fluid springs of a fluid suspension system at a manifold of the fluid suspension system of the vehicle during loading of the vehicle;

[0008] - determining a first load profile based on the fluid pressure, wherein the first load profile comprises a coordinate mapping between first discrete portions of the vehicle load and first locations within the vehicle cargo hold;

[0009] - determining a second load arrangement based on the loading criteria, wherein the second load arrangement comprises a second coordinate mapping between second discrete portions of the vehicle load and second locations within the vehicle cargo hold;

[0010] - determining a loading instruction set based on the second load arrangement and the first load arrangement; and

[0011] - providing said set of loading instructions to a vehicle user.

[0012] Determining a set of loading criteria includes receiving weight restriction data associated with a geographic location of the vehicle along a planned route of the vehicle.

[0013] The method also includes determining a dynamic model of vehicle operation, wherein the dynamic model is based on the loading criteria.

[0014] The method further includes determining the second load profile based on the dynamic model and the first load profile, and generating a loading instruction based on a difference between the first load profile and the second load profile.

[0015] The first discrete portion and the second discrete portion of the vehicle load are the same portion of the vehicle load.

[0016] The fluid spring assembly is driven in response to the arrangement of at least one of the first load portion and the second load portion within the cargo hold so as to minimize an angular difference between a vector perpendicular to the cargo hold bottom and a gravity vector.

[0017] The method further includes monitoring the pressure values ​​in substantially real time during vehicle loading, determining a real-time load profile, generating a comparison between the real-time load profile and a second load profile, and providing a notification to a user based on the comparison, wherein the notification indicates a degree of user compliance with the set of loading instructions.

[0018] A method of analyzing and managing a vehicle load carried by a vehicle having a fluid suspension system, the method comprising:

[0019] - sampling a fluid pressure corresponding to a set of fluid springs of a fluid suspension system at a manifold of the fluid suspension system, wherein the set of fluid springs supports the vehicle load at a plurality of actuation points;

[0020] - determining an existing stiffness profile based on the fluid pressure, the existing stiffness profile comprising stiffness values ​​associated with each fluid spring in the set of fluid springs;

[0021] - determining context-dependent data sets substantially in real time during vehicle operation;

[0022] - determining a desired stiffness distribution based on said context-dependent data set;

[0023] - automatically controlling a set of fluid springs at a plurality of driving points based on the desired stiffness profile, wherein controlling the set of fluid springs comprises setting a stiffness value of a fluid spring associated with each driving point of the plurality of driving points.

[0024] The context-dependent dataset includes predicted terrain features, and determining the context-dependent dataset is based on a planned route of the vehicle and terrain features associated with the planned route.

[0025] The predicted terrain feature includes a sloped road, and wherein automatically controlling the fluid spring group includes: setting a first stiffness value for a first subset of multiple driving points on a first side of the vehicle, and setting a second stiffness value for a second subset of the multiple driving points on a second side opposite to the first side of the vehicle.

[0026] The context-dependent data set includes an indication that the vehicle is loaded, and wherein automatically controlling the fluid spring set includes maintaining a base surface of the vehicle cargo hold substantially perpendicular to a gravity vector during loading, wherein the vehicle load includes discrete load portions.

[0027] The method also includes automatically deploying the lift axle using the fluid suspension system when a deployment criterion is met.

[0028] The deployment criteria includes the desired stiffness profile including a stiffness value exceeding a stiffness threshold at a fluid spring of the set of fluid springs.

[0029] The deployment criteria include a planned route for the vehicle, the route including travel of the vehicle in a geographic area associated with regulatory rules, the regulatory rules including weight limits for each axle.

[0030] The method also includes automatically retracting the lift axle using the fluid suspension system if a retraction criterion is met.

[0031] The retraction criteria include a planned path of the vehicle including a turn exceeding a turn angle threshold; wherein automatically retracting the lifting axle is performed within a time period approaching or prior to the vehicle turning.

[0032] The method also includes automatically adjusting fluid pressure in at least one tire of the vehicle using the fluid suspension system based on the fore-aft data.

[0033] The fore-aft data includes the total weight of the vehicle load.

[0034] The method also includes providing a notification to a vehicle user, wherein the notification includes a portion of the vehicle load supported by each fluid spring in the fluid spring group.

[0035] Providing the notification includes graphically presenting the notification on a device associated with the user, and further includes receiving input from the user at the device and driving the set of fluid springs based on the input. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flowchart of a variation of this approach;

[0037] Figure 2 are side views of various vehicle types and configurations in which the method may be implemented;

[0038] Figure 3 is an exploded view of an example of this system;

[0039] Figure 4 is a schematic diagram of the reaction forces due to a possible overload in a vehicle;

[0040] Figure 5 is a schematic diagram of example computing system components that may implement variations of the present method;

[0041] Fig. 6A -B is an example effect diagram depicting a portion of an example of the present method;

[0042] Figure 7 is a suspension pressure-time line graph depicted according to an embodiment of a variation of the method;

[0043] Figure 8 is a flowchart of a specific embodiment of the method; and

[0044] Fig. 9 It is a flow chart of another specific embodiment of the method. DETAILED DESCRIPTION

[0045] The following description of the preferred embodiments is intended to enable those skilled in the art to understand and use the present invention, rather than to limit the scope of the present invention.

[0046] 1. Overview

[0047] like Figure 1 As shown, the method 100 for vehicle load management includes: determining a vehicle state parameter S110; determining a current state of a vehicle suspension system S120; determining a desired state of the vehicle suspension system based on the vehicle state parameter S130; and converting the current state of the vehicle suspension system into a desired state S140. The method 100 is used to manage the load carried by the vehicle (such as the vehicle load), and is capable of manipulating (such as actuating) the suspension system of the vehicle, and / or instructing the vehicle operator to arrange the vehicle load so that the vehicle suspension system is converted to an ideal state. The method 100 can also actively control the posture of the vehicle (such as roll angle, pitch angle, etc.) by controlling the stiffness and / or suspension height of the suspension system. The method can also be used to determine a dynamic model of vehicle operation based on vehicle load characteristics. In addition, the method 100 has any other suitable vehicle load management functions.

[0048] Preferably, the method 100 is implemented in a vehicle configured to carry cargo in a cargo hold. Figure 2 As shown, the vehicle can be a commercial truck (e.g., a tractor trailer, a hauler, a drilling vehicle, a truck, a professional truck, a rear-load vehicle, a front-load vehicle, a dry van / refrigerated trailer, a professional trailer, etc.), a recreational vehicle (e.g., a camper, a motorhome, a trailer, a caravan, a motorhome travel trailer, an RV fifth wheel trailer, etc.), an oversized truck, and any other suitable vehicle, and can include any suitable number and configuration of auxiliary lifting axles (e.g., lifting axles, lowering axles, etc.). In an optional embodiment of the method 100, the vehicle can be a private car (e.g., a sedan, a minivan, a station wagon, etc.). In the case where the vehicle is a tractor trailer, preferably, the cargo hold is a trailer. In the case where the vehicle is a recreational vehicle, preferably, the cargo hold is the interior of the vehicle. But optionally or alternatively, the cargo hold can be any suitable part of the interior of the vehicle.

[0049] Preferably, the method 100 is at least partially implemented by a system including an electronic control unit (ECU) 200, which is configured to control a fluid-based suspension system (e.g., a liquid suspension system, an air suspension system, a pneumatic system, etc.). The suspension system may include a primary suspension system (e.g., a suspension system corresponding to a drive shaft or a main shaft and a main drive shaft) and a secondary suspension system (e.g., a lift shaft suspension system, an auxiliary suspension system, etc.). Figure 3As shown, preferably, the electronic control unit 200 includes a housing 210, a printed circuit board assembly (PCBA) 220, a valve stop plate 230, a valve 240, a manifold 250, a pressure sensor 260 and an accessory 270. Preferably, the system 200 integrates the valve, the sensor and the PCBA into a sealed module, which is used to control any device driven by fluid pressure (for example, according to a variation and / or part of the method 200). ECU200 can also be used to monitor the supply pressure (for example, the pressure from the vehicle compressor), and can limit the operation of the system when the supply pressure is higher than a threshold value (for example, an airlock pressure protection threshold). ECU200 can also use any appropriate method (for example, using pulse width modulation to adjust the inflow and outflow drive points) to open the valve to inflate or deflate the control point (for example, an air spring, a load bag, a lifting bag, etc.). ECU200 can also use an auxiliary valve (for example, driven by a main valve) to increase the system response speed (for example, where the auxiliary valve has a higher flow rate than the main valve). ECU200 can also be used to detect and report leakage rates of parts of the fluid suspension system (e.g., via a CAN bus, or a communication protocol such as Bluetooth, radio, etc.). ECU200 can also be used to connect to a remote device (e.g., Bluetooth) to transmit system information and receive user input (such as control instructions). ECU200 can also be used to connect to a vehicle computing and processing structure (e.g., a CAN bus) and use the data (omnidirectional data) collected therefrom (e.g., vehicle speed, ABS active alarm, steering wheel angle, geographic location, etc.) to implement one or more parts of method 100. ECU200 can also be used to monitor an on-board (e.g., integrated with the ECU) three-axis accelerometer (or other inertial measurement unit) to determine vehicle attitude (e.g., driving height, driving angle, etc.) and / or vibration characteristics during vehicle operation (e.g., excessive vibration caused by unbalanced and / or out-of-round tires, etc.). ECU200 can also be used to monitor other vehicle sensor outputs (e.g., brake pad wear sensors) and report the output results to the vehicle computing and processing structure (e.g., transmitting the output data to the CAN bus). In addition or alternatively, ECU200 can have any other reasonable functions.

[0050] In the variant system, ECU200 substantially includes the components described in the text of U.S. patent application Ser. No. 15 / 712,995 filed on Sep. 22, 2017, and the entire contents of which are incorporated herein by reference. However, in addition or alternatively, the method 100 may be implemented in conjunction with a system including any other suitable electronic control unit.

[0051] In some variations, method 100 includes controlling tire pressure using system 200, which may be configured and used substantially as described in U.S. patent application Ser. No. 15 / 805,015, filed Nov. 6, 2017, and the entire contents of which are incorporated herein by reference. However, in optional variations, method 100 may also appropriately control tire pressure and / or omit tire pressure control.

[0052] In some variants, method 100 includes the use of positioning (e.g., location data). Positioning can be a set of geographic coordinates (e.g., longitude and latitude), a place name (e.g., county, city, landmark, intersection, etc.), a physical street address, distance from a given location, presence within a specified radius of a given location, a graphical depiction on a map, or any other appropriate location expression. Geolocation includes geocoding to find relevant longitude and latitude from other geographic data. Additionally or optionally, geolocation also includes reverse geocoding to encode longitude and latitude coordinates into a readable address or place name. Location information can be determined based on GPS coordinates provided by the device, triangulation between mobile phone towers and public base stations (e.g., assisted GPS), Wi-Fi connection location, domain name query service (WHOIS) performed on IP addresses or MAC addresses, global system for mobile communications (GSM) / code division multiple access (CDMA) cell addresses (IDs), user self-reported location information, or any other suitable means. The positioning system can be a GPS system, a cellular tower triangulation system, a triangulation system, a beacon system, or any other suitable positioning system.

[0053] like Figure 5 As shown, in other variants, method 100 can be performed in combination with a mobile device, a remote computing system, and a vehicle computing processing system in addition to the ECU. The user device includes a tablet computer, a smart phone, a mobile phone, a laptop, a watch, a wearable device (such as glasses), or any other suitable device. The user device includes a power storage device (such as a battery), a processing system (such as a CPU, a GPU, a memory, etc.), a user output device (such as a display, a speaker, a vibration device, etc.), a user input device (such as a keyboard, a touch screen, a microphone, etc.), a positioning system (such as a GPS system), a sensor (such as an optical sensor, such as a light sensor and a camera; a direction sensor, such as an accelerometer, a gyroscope, an altimeter; an audio sensor, such as a microphone, etc.), a data communication system (such as a Wi-Fi module, a BLE, a cellular module, etc.) or any other suitable component.

[0054] The output devices include: displays (such as LED displays, OLED displays, LCDs, etc.), speakers, lights (such as LEDs), tactile outputs (such as tixel systems, vibration motors, etc.) or any other suitable output devices.

[0055] The input device includes: a touch screen (such as a capacitive touch screen, a resistive touch screen, etc.), a mouse, a keyboard, a motion sensor, a microphone, a biometric input, a camera or any other suitable input device.

[0056] The communication system includes one or more radio devices or any other suitable components, which can be a long-range communication system, a short-range communication system, or any other suitable communication system. The communication system facilitates wired and / or wireless communication. For example, the communication system includes: 802.11x, Wi-Fi, Wi-Max, WLAN, NFC, RFID, Bluetooth, low-power Bluetooth, long-range low-power Bluetooth, ZigBee, cellular communication (such as 2G, 3G, 4G, LTE, etc.), radio frequency (RF), microwave, infrared, audio, optical, wired connection (such as USB) or any other suitable communication module or combination.

[0057] The sensors of the system, device and / or vehicle include: cameras (such as line-of-sight, multi-spectral, hyperspectral, infrared, stereoscopic, etc.), orientation sensors (such as accelerometers, gyroscopes, altimeters), acoustic sensors (such as microphones), optical sensors (such as photodiodes, etc.), temperature sensors, pressure sensors, flow sensors, vibration sensors, proximity sensors, chemical sensors, electromagnetic sensors, force sensors or any other appropriate type of sensor.

[0058] Preferably, the power supply is a fixed power supply. However, the power supply may also include: a power supply connected to the vehicle battery by wire, a wireless connection power supply (such as inductive charging, RFID charging, etc.), a battery (such as a secondary or rechargeable battery, a primary battery, etc.), an energy collection system (such as a solar cell, a piezoelectric system, a thermoelectric body, a thermoelectric element, etc.), or any other suitable system.

[0059] The positioning system includes: a GPS unit, a GNSS unit, a triangulation unit that triangulates the device's location between mobile phone towers and public base stations (such as assisted GPS), a Wi-Fi connected positioning unit, a WHOIS unit (for example, based on IP address and MAC address), a GSM / CDMA cell identifier, autonomously reported location information, or any other suitable positioning module.

[0060] Preferably, the method is performed in whole or in part by an ECU in system 200. However, optionally, it may also be performed by a local application on a user device, a server, a web application on the user device, or any other suitable device. Preferably, the user device is a mobile device associated with a user, including: a mobile phone, a laptop, a smart phone, a tablet computer, or any other suitable mobile device. Preferably, the user device is connected to a server, wherein the connection is preferably a wireless connection, such as Wi-Fi, a cellular network service, and any other suitable wireless connection; a near field communication connection, such as radio frequency, Bluetooth, and any other suitable near field communication connection; or a wired connection, such as a local area network (LAN) line. Optionally, the user device may act as a server, for example in a distributed network system. The method may be performed by one or more servers, wherein the server may be stateless, stateful, or have any other suitable configuration or attribute.

[0061] In a variant of the present invention, the method 100 module can be implemented as a module group and / or part thereof, wherein the module group is implemented at a computing system (e.g., an ECU, a mobile device, an alternative computer system associated with a vehicle, etc.). Each module in the module group can utilize one or more of the following functions: supervised learning (e.g., using logistic regression, using a back-propagation neural network, using a random forest, a decision tree, etc.), unsupervised learning (e.g., using an Apriori algorithm, using K-means clustering), semi-supervised learning, reinforcement learning (e.g., using a Q learning algorithm, using a temporal difference learning algorithm), and any other suitable learning method. Additionally or optionally, each module can be: a probability module, a heuristic module, a deterministic module, or any module utilizing other suitable computational methods, machine learning methods, or a combination thereof.

[0062] Each module may be validated, verified, enhanced, calibrated, or updated based on newly received, updated measurement data; past measurements recorded during operation; historical measurements recorded during past operations; or updated based on any other suitable data. Each module may be run or updated: once; at a predetermined frequency; each time the method is executed; each time an unexpected measurement value is received; or at any other suitable frequency. The set of modules may be run or updated in parallel with one or more other modules continuously at different frequencies, or at other suitable times. Each module may be validated, verified, enhanced, calibrated, or updated based on newly received, updated, previous data, or updated based on any other suitable data. Each module is run or updated in response to a determination that an actual result is different from expected; or at any other suitable frequency.

[0063] 2. Beneficial effects

[0064] The inventors have discovered several disadvantages of conventional suspension systems. First, the pressure regulator is typically set to full load pressure rather than being optimized for partial load. Second, when a vehicle includes a lift axle, actuation (e.g., raising, deploying) of the lift axle is typically performed manually, relying on the driver to remember to raise and / or deploy the lift axle. Third, because the actuation of the lift axle is manual, the deployment and / or raising of the lift axle may be inconsistent for different drivers, and may require the driver to constantly explain and answer road conditions, route conditions, and / or load conditions (e.g., executing a turn) that cause the lift axle to be deployed and / or raised. Fourth, conventional pneumatic height control systems are designed with response delays to reduce air consumption and improve fuel economy, but this delayed control response slows down the vehicle's ability to fully lift the lift axle. Fifth, some vehicles do not have adjustable suspension at all, and therefore suffer from asymmetric axle loads.

[0065] Variations of method 100 and / or system 200 can provide benefits and / or advantages.

[0066] First, various variations of the system can achieve automatic suspension adjustment and / or automatic deployment of the lift axle, thereby improving regulatory compliance, optimizing fuel consumption, and improving vehicle performance. Second, various variations of the system and method provide a convenient way for users (e.g., first-time users, novice users, etc.) to smoothly load the vehicle by instructing the user on how to adjust the load in the vehicle (e.g., arrange the load) in real time or near real time, and / or by dynamically adjusting the vehicle support structure (e.g., tires, suspension, jacks, etc.) to accommodate load imbalances. However, the system and method can have any suitable beneficial effect.

[0067] In a first example, the method may enable non-conventional drivers (e.g., non-professional drivers) of tractor-trailers (e.g., vehicles used to move cargo, such as flatbed trailers, recreational vehicles, mid-axle motorhomes, and tow trucks, etc.) to avoid improper load arrangement by measuring the load arrangement during and after vehicle loading and providing instructions to the driver on how to properly arrange the load.

[0068] In a second example, the method may enable a commercial truck driver to maximize the efficiency of distributing the vehicle load during loading. For example, the method includes providing the driver with real-time updates on the weight of the load carried by each axle during loading, thereby enabling the driver to comply with the total weight limit and each axle weight limit on his planned route. In another example, the method includes maintaining a level setting of the trailer when the vehicle is loaded with a dispersed load unit (such as a pallet), by automatically actuating the air suspension system in response to the changing load distribution in the cargo hold, thereby preventing the dispersed load unit from sliding, rolling or moving in the cargo hold during loading.

[0069] Second, variations of the systems and methods may enable better driver focus, maximize load on the drive axle to improve traction, reduce tire wear, improve fuel economy, diagnose and / or predict maintenance or configuration costs, and improve regulatory compliance (e.g., bridge code compliance across one or more regions), all through the vehicle's automated lift axle deployment and / or controlled fluid suspension system.

[0070] Third, variants of the system and method can monitor performance characteristics (e.g., integrity, wear, etc.) of system components (e.g., tires, fluid springs, fluid jacks, etc.) and report them to a user or other entity associated with the vehicle. These characteristics can enable the vehicle and / or its components to be serviced (e.g., repaired, replaced) before a failure or an undesirable decrease in component performance occurs. For example, variants of the system and method can: detect the temperature of a component (e.g., internal temperature, fluid temperature, housing temperature) to determine a thermal cycle history associated with the component; sense vertical acceleration and pressure fluctuations and determine a rough and / or smooth road operation history; detect pressure in suspension elements (e.g., springs, tires) to determine changes in load over time; and use the above characteristics (e.g., in combination with data from component manufacturers) to estimate the remaining life of components (e.g., tires, air springs, dampers, bushings, etc.) and report the remaining useful life of the component to a user or other entity responsible for maintaining the vehicle system.

[0071] However, variations of the methods and / or systems may also provide any other suitable advantages and / or benefits.

[0072] In one specific example, a truck with a controllable air suspension system may be traveling along a route defined by a series of map coordinates (e.g., determined by GPS). A computing system controlling the air suspension system determines (e.g., via the map coordinates) that the truck has arrived and / or is about to arrive at an intersection, and that the truck may need to raise the lift axle to make a turn (e.g., a turn angle greater than a threshold, a turn with a sharpness exceeding a threshold, and other turns). The method automatically raises the lift axle in preparation for the turn. In a related specific example, the method may determine that the truck has arrived at a loading and unloading warehouse or other destination where trailer / load unloading operations may be performed, and automatically raise the lift axle in preparation for the operation, and / or automatically adjust the suspension loading height (e.g., using load data collected from air springs and / or jacks to inform an operator how to optimize existing or future vehicle load distribution).

[0073] In another specific example, the method includes automatically changing the suspension loading height in real time or near real time based on terrain data related to the planned route. Trucks (such as autonomous and / or platoon trucks) can travel with the lowest possible suspension loading height to achieve maximum aerodynamic efficiency while leaving enough suspension space to allow the truck to travel on rough and / or highly variable terrain without bottoming out. The method includes determining terrain roughness (e.g., based on known terrain features along the vehicle route) and automatically increasing the suspension loading height in the planned route area containing rough terrain. In a related example where multiple trucks form a platoon, the lead vehicle first experiences (e.g., detects) the terrain feature, and the method then transmits the terrain feature to subsequent vehicles in the platoon and automatically adjusts the suspension loading height of the subsequent vehicles accordingly. In this example, the method includes providing terrain data to an autonomous route and group controller (e.g., a teleoperator, a remote server, etc.), and collecting the terrain data using sensors of the air suspension system (e.g., suspension loading height, pressure, and / or accelerometer sensors). The method can also provide terrain data to navigation products (such as Waze, Google Maps, etc.) so that the user can understand the terrain features of the route, and automatically adjust the suspension loading height to avoid obstacles if the user's vehicle includes a controllable suspension system, or adapt the suspension to the terrain features in other suitable ways.

[0074] In another specific example, the method includes automatically optimizing the placement and suspension height of the lifting axle according to real-time conditions during driving (such as terrain conditions, weather conditions, etc.). Based on the planned route (such as retrieved from a database, determined from an onboard GPS computing system, etc.) and combined with meteorological data along the route (such as retrieved from a weather forecast database, measured using an onboard weather sensor, etc.), the method can optimize (such as by driving the air suspension system) the vehicle height and / or the load on the lifting axle and the drive axle. In one specific embodiment, the weather data can indicate an icy environment, and the method can increase the percentage of the load borne by the drive axle to increase the traction of the tire at the drive axle (for example, increase the stiffness of the suspension supporting the drive axle relative to the stiffness of the suspension supporting the non-drive axle). In another specific embodiment, the weather data can indicate a snowy environment, and the method can balance the loads of all axles (e.g., drive axles and non-drive axles) to improve the stability of the vehicle when driving at high speeds (e.g., highway speeds in the United States are 45-75 miles / hour or any suitable speed) and in snowy environments. In a related specific embodiment, the method can actively adjust the relative stiffness of the air suspension of each axle, and / or fully or partially lift a liftable axle (such as a lift axle) for any suitable purpose, such as improving fuel economy by transferring more load to a lift axle with low rolling resistance tires, improving suspension engagement on rough terrain by fully lifting a lift axle, etc.

[0075] In another specific example, the method includes monitoring whether the vehicle is level (e.g., whether the vehicle is level relative to the gravity vector, the level of the bottom of the vehicle cargo compartment, etc.) on an on-board level sensor, wherein the sensor includes: a bubble level, a digital level, an accelerometer, a suspension height sensor that measures the angular difference between the road plane and the vehicle body plane, etc. In the case where the vehicle is not level, the net force direction of each part of the load (e.g., the load vector) may change, so the method (e.g., a method implemented at a control system) is able to determine the vehicle level and report the load vector to the user and / or dynamically control the suspension system based on the load vector (e.g., to adjust the load vector, maintain the load vector, etc.).

[0076] In some configurations, the trailer can be loaded while disconnected from the towing vehicle (e.g., tractor, pickup truck, etc.), and it is still necessary to monitor the load distribution and inform the operator of the optimal load distribution and recommended steps to achieve the optimal load distribution. In this configuration, the method can monitor and control trailer supports (e.g., landing gear, tongue jack, etc.) driven by compressed fluid (e.g., pneumatic air springs). Such supports can be considered part of the vehicle suspension system (e.g., vehicle air suspension system).

[0077] 3. Methods

[0078] As described above, the method 100 for vehicle load management includes: determining a vehicle state parameter S110; determining a current state of a vehicle suspension system S120; determining a desired state of the vehicle suspension system according to the vehicle state parameter S130; and converting the current state of the vehicle suspension system into a desired state S140. Preferably, all or part of the steps of the method are performed by an ECU, but additionally or alternatively, they may also be performed by a vehicle, a user device (e.g., a smartphone), a remote computing system (e.g., a server system), or any other appropriate system. The method may be performed upon detection of a triggering event (e.g., detecting a door opening, vehicle power-on, vehicle movement, suspension loading or unloading, manual selection of a button or icon, or any other appropriate triggering event), periodically, before or after vehicle loading, during loading, or at any appropriate time.

[0079] Preferably, the load arrangement describes the load mass (weight) (e.g., including as indicated by data) as a function of its position within the vehicle cargo compartment, and is capable of describing that function at any suitable resolution (e.g., a continuous function of position, a discrete function of position corresponding to the position of each suspension element, a binary function of "front" and "rear" positions, a coordinate mapping of load portions to load positions, etc.).

[0080] Module S110 includes: determining a vehicle state parameter, which is used to determine data of the vehicle state that is closely related to vehicle load management, so as to serve as an input to subsequent modules of the method 100 . The vehicle state parameters include: the total weight of the load in the vehicle, the total weight of the load to be loaded into the vehicle (such as the outside of the vehicle), the arrangement of the load in the vehicle (for example, the weight as a function of the position in the cargo compartment or other internal cavity of the vehicle), the operating range of the suspension (such as the minimum and maximum values ​​of each air spring pressure, the minimum and maximum values ​​of the stroke of each suspension element, etc.), the operating range of other components (such as the minimum and maximum values ​​of the internal tire pressure, the maximum load of each axle), the planned route of the vehicle (such as the set of geographical locations passed by the vehicle between its starting point and end point), the geographical location of the vehicle, traffic conditions related to the vehicle's location and / or planned route (such as speed limit, actual driving speed, weight limit, road and bridge axle limit, etc.), weather conditions related to the vehicle's location and / or planned route (such as rain, sleet, snow, hail, wind, high temperature, etc.), terrain features related to the vehicle's location and / or planned route (such as road inclination angle, road surface quality, potholes, speed bumps, etc.), a physical model of vehicle operation (for example, a dynamic model of system response based on the distribution of load in the vehicle during vehicle operation and operation), and any other suitable parameters. In addition or alternatively, the vehicle condition parameter may include any appropriate combination of the above parameters. The vehicle state parameter may be a data set, a single parameter value, a set of parameter values, or any other suitable data structure. The vehicle state parameter may be determined by the following devices: vehicle sensors (e.g., pressure sensors coupled to the internal reservoir of each element of the fluid suspension system, height sensors for detecting the loading height of the vehicle suspension, accelerometers, vibrometers, GPS sensors, etc.), user input devices (e.g., user interfaces, touch screens coupled to the ECU, mobile devices associated with the user and coupled to the ECU, etc.), remote computing systems (e.g., remote databases capable of receiving vehicle state parameters from the vehicle), on-board algorithms (e.g., algorithms executed on the ECU, algorithms executed on another computing system of the vehicle, etc.), and any other suitable devices.

[0081] In a specific example, module S110 is capable of receiving vehicle state parameters at the ECU. In one example, the vehicle state parameters include data associating fluid spring pressure with load (e.g., a lookup table, a function associating load with pressure, etc.). In another example, the vehicle state parameters include a calibration data set that includes baseline pressures of various elements in the fluid suspension system when the vehicle is unloaded (e.g., for determining the load added during loading). In another example, the vehicle state parameters include the number of axles. In another example, the vehicle state parameters include a vehicle identification number (VIN), and the method uses the VIN (e.g., from a lookup table) to retrieve vehicle data (e.g., additional vehicle state parameters). However, module S110 may also receive and / or determine any other suitable internal and / or external parameters associated with the vehicle.

[0082] Module S110 includes module S111, which includes: determining a set of loading standards. Module S111 is used to determine a set of standards that the load distribution in the vehicle cargo compartment should meet to determine the desired state of the vehicle suspension system (such as module S130). The loading standards can be determined by calculation, selection, retrieval or other methods. The loading standards can be determined based on the following factors: vehicle make and / or model, driver, vehicle operation history (such as age, wear, etc.), geographical route, weather (such as current weather, predicted weather), wear component parameters (such as tire age, tread wear, etc.), suspension type, system pressure or any other suitable parameter. The loading standards include: weight distribution of each axle, weight limit of each axle, loading frequency, loading order (such as from back to front, from left to right) or any other suitable loading standards. The loading standards can be determined by the ECU, or retrieved from a remote computing system (such as directly using a user device as an intermediary, etc.), or determined in other ways. In the first example, the determination of the loading standards includes receiving weight limit data associated with each axle of the vehicle (such as each axle in a set of axles of the vehicle). In one related example, the set of loading standards can be associated with the geographic location of the vehicle (e.g., loading standards associated with valid standard codes in the geographic location of the vehicle). In another related example, the set of loading standards can be associated with a planned route of the vehicle (e.g., a route including a total weight limit and a weight limit per axle, etc.).

[0083] A variant of module S111 includes: determining a dynamic model of vehicle operation. Preferably, the dynamic model is at least partially based on the load characteristics of the vehicle (such as load arrangement, total weight, etc.). Preferably, the dynamic model is a dynamic model, but alternatively, it may also include: optimization equations, a set of rules that map the load weight at each location in the vehicle cargo compartment to steering responsiveness or other vehicle operating characteristics, the vehicle's operating envelope (for example, a set of vehicle state parameters that allow the vehicle to operate in an ideal or controllable manner), and any other physical model suitable for vehicle operation. For example, the dynamic model of vehicle operation can be based on the arrangement of the vehicle load in the cargo compartment. The arrangement of the vehicle load will affect the handling performance of the vehicle; for example, Figure 4 As shown, the load toward the rear of the trailer causes an upward force on the rear wheels of the trailer, thereby reducing the traction and / or performance of the vehicle, especially when the rear wheels of the trailer are drive wheels. The determination (such as selection, calculation, acquisition, etc.) of the dynamic model can be based on the following factors: vehicle type, driver or operator, route (such as terrain, operations required along the route), weather (such as current weather, predicted weather, historical weather, etc.), weight of the load in the vehicle, arrangement of the load in the vehicle, or determined by other factors. The dynamic model can output: a second load arrangement (such as a preferred load arrangement, an optimal load arrangement), a binary output indicating whether the vehicle can operate ideally (such as pass / fail), instructing the user how to arrange the load so that the vehicle operating parameters reach the ideal range (such as related to steering response, braking response, uncontrolled bending avoidance, etc.), and any other suitable output. The dynamic model can be constructed and / or implemented in the following forms: a neural network, an optimization equation, a discrete model, or any other suitable structure.

[0084] Module S110 includes module S112, which includes: determining a data set related to the context. Module S112 is used to determine parameters related to the vehicle operating environment. The context-related data set includes: any of the above-mentioned vehicle state parameters, historical data related to the vehicle (such as maintenance records, performance history, etc.), data related to the physical environment of the vehicle (for example, the position of surrounding vehicles relative to the vehicle or road characteristics, traffic characteristics of the area where the vehicle is located, brightness around the vehicle, the proximity of pedestrians to the vehicle, etc.), and any other appropriate data related to the vehicle environment. Preferably, module S112 is executed substantially in real time. However, additionally or optionally, it can also be executed asynchronously according to any delay in response to a trigger, or at any other suitable time point or time period. The context-related data set can be determined by an on-board sensor (as described above), received from a user (as described above), or determined by other appropriate means. Preferably, module S112 is executed during vehicle operation, including vehicle movement (such as vehicle driving), vehicle loading and / or any other appropriate vehicle state. The context-dependent data sets may be determined based on factors such as the planned route of the vehicle, the location of the vehicle, the operating conditions of the vehicle (e.g., dynamic changes in vehicle operating characteristics, increasing or decreasing tactile or auditory feedback to the user during vehicle operation, etc.), and any other suitable factors.

[0085] A variant of module S112 includes: determining a front-back related data set based on the planned route of the vehicle and the terrain features associated with the planned route. In this variant, preferably, the front-back related data set includes predicted terrain features (e.g., inclined roads, turns, etc.).

[0086] Module S120 includes: determining the current state of the vehicle suspension system, that is, establishing a reference state of the vehicle load distribution to determine the transition in the subsequent modules of the implementation method 100. Preferably, the state of the vehicle suspension system includes the instantaneous force provided by each suspension element (such as air springs, air jacks, etc.) in the system and the mechanical energy required for the instantaneous force, so that the load characteristics supported by the suspension system can be determined based on the force and / or mechanical energy. However, additionally or optionally, the state of the vehicle suspension system may also include: data based on the above-mentioned force and / or work, load distribution between suspension elements (such as air springs) of the suspension system, binary instructions on whether the vehicle is loaded (for example, whether the cargo has been loaded into the vehicle, whether it has been unloaded from the vehicle, etc.), the stiffness of the suspension system (for example, the stiffness of each air spring, the pressure required for each air spring to maintain the stiffness, etc.), whether the suspension system is in an active or passive state (for example, whether the air is actively compressed in an air suspension system), and any other suitable data related to the state of the vehicle suspension system. Module S120 may be executed by an ECU, a fluid suspension system, a pressure sensor in a pressure manifold, a vehicle, or any other suitable system. In one variant, module S120 may be executed periodically, asynchronously, and / or according to any other suitable time characteristic upon detection of a triggering event. Triggering events include crossing a virtual geo-fence (e.g., along a vehicle route), an output of a vehicle sensor exceeding a threshold (or falling below a threshold, or exceeding a range of preset values), receiving user input, and any other suitable triggering event.

[0087] Module S120 includes module S121, which includes: sampling at the manifold of the fluid suspension system of the vehicle when it is loaded, and sampling the fluid pressure of a group of fluid springs in the fluid suspension system. Module S121 is used to directly measure the system pressure in the fluid springs (such as air springs, pneumatic actuators, hydraulic springs, actuators, etc.) supporting the vehicle load, so as to determine the load (such as weight) carried by each spring and the total load weight in the vehicle cargo compartment. The fluid springs supporting the vehicle load include: vehicle suspension springs, jacks (for example, to control the installation height of the RV or trailer to the tractor), air springs, pneumatic jacks, landing gear that extends or retracts the fluid spring / jack, air bags (such as inner tubes) of vehicle tires, or any suitable fluid spring group.

[0088] Module S120 includes module S122, which includes: determining a first load arrangement based on the set of fluid pressures, that is, determining how the cargo (such as load, mass) is distributed in the trailer. In one variant, the first load arrangement includes a coordinate mapping between a first discrete portion of the vehicle load and a first position in the vehicle cargo compartment. The function of module S122 is to calculate the load distribution in the cargo compartment based on the fluid pressure distributed at points around the vehicle chassis (such as between the cargo compartment and the axle). In this variant, each fluid manifold and / or pressure sensor is mapped to a preset vehicle position (such as a trailer position), where the mass of each trailer position can be calculated by the corresponding pressure sensor measurement value. In a second variant, the first load arrangement is determined by recording a set of external images of the loaded vehicle. The relative suspension height can be determined based on the distance between the wheels (for example, using segmentation, feature detection or other computer vision techniques to extract data from the image), the mass of the load can also be determined based on the change in suspension height, and the load distribution can be determined based on the relative height of the suspension elements. However, the load arrangement can be determined by other means.

[0089] Module S120 includes module S123, which includes: determining an existing stiffness distribution based on the fluid pressure group, the existing stiffness distribution including a stiffness value associated with each fluid spring in the fluid spring group. Module S123 is used to calculate the impact of the load in the cargo hold in the form of a spring stiffness, and the spring stiffness is an adjustable function of the controlled fluid pressure in each spring. Module S123 can be performed by sampling the pressure at each air spring (for example, at the reservoir port of each air spring, at the pressure line coupled to each air spring, at the manifold coupled to each air spring, etc.), and associating the sampled pressure and the spring stiffness (for example, stored in a database via a lookup table). Preferably, the stiffness value is a spring constant (such as an adjustable spring constant) associated with a suspension element (such as an air spring); however, the stiffness value may include any relevant dynamic parameter that controls the operation of the suspension element (such as shock absorber settings, buffer resistance, inherent stiffness, etc.). Preferably, the stiffness distribution is related to the load distribution in the vehicle cargo compartment (e.g., the stiffness is related to the internal pressure of the fluid spring, which is related to the load distribution); however, in a variant, the stiffness distribution can be independent of the load distribution and can also be independently set (e.g., via a controllable manifold). The S123 module can also be executed in other suitable ways.

[0090] Module S130 includes: determining the desired state of the vehicle suspension system, that is, identifying the state of the required vehicle suspension system to obtain one or more criteria based on the vehicle state parameters. The desired state of the vehicle suspension system can be defined in a manner related to the existing state of the vehicle suspension system mentioned above, as well as in any other suitable manner. Preferably, the desired state is determined according to the vehicle state parameters (as described above), but additionally or alternatively, it can also be determined according to a set of loading standards, a set of data related to the front and back, and / or any other suitable basis. Preferably, the desired state is determined by the ECU, but additionally or alternatively, it can also be determined by any suitable computing system and / or user associated with the vehicle. In some variants, the desired state of the vehicle suspension system is the same as the existing state (such as the same existing and expected load arrangement, the same existing and expected stiffness distribution, etc.); in these cases, converting the existing state of the vehicle suspension system to the desired state means: passively maintaining the vehicle suspension system in the existing state, or providing a suspension state to be maintained (for example, providing a user with a loading instruction to retain the existing configuration, arrangement and / or load distribution, etc.).

[0091] Module S130 includes module S131, which includes: determining a second load arrangement based on the set of loading standards. The second load arrangement includes a second coordinate mapping between a second discrete portion of the vehicle load and a second position in the vehicle cargo compartment. The function of module S131 is to identify the in-vehicle load arrangement that meets the set of loading standards. For example, when the set of loading standards includes the maximum weight that each axle can bear, module S131 can determine a load arrangement (which may be different from or the same as the first arrangement) for load distribution that does not exceed the maximum weight that each axle can bear. However, additionally or optionally, module S131 can also determine the second load arrangement based on the set of loading standards in any other suitable manner.

[0092] A variation of module S131 includes calculating the second load arrangement using a dynamic model (eg, determined by module S111). In this variation, the first load position (eg, determined by module S122) is an input to the dynamic model.

[0093] In a specific example of modules S121 and S131, determining the second load arrangement includes determining a new position for the first discrete portion of the vehicle load (e.g., rearranging the first discrete portion of the vehicle load, the first discrete portion and the second discrete portion of the vehicle load are the same, etc.).

[0094] Module S130 includes module S132, which includes: determining a desired stiffness distribution. Module S132 is used to determine the stiffness value associated with each suspension element (such as an air spring), which corresponds to the desired state of the suspension system. Module S132 can be executed based on a set of related data, a set of loading standards, any other vehicle condition parameters, and any other suitable basis. Preferably, the desired stiffness distribution is a series of stiffness values ​​determined thereby. However, additionally or alternatively, it can also be a set of pressure values ​​(for example, corresponding to the stiffness value of a pressurized air spring), a range of stiffness values ​​associated with suspension elements having any suitable correspondence (such as one-to-one, one-to-many, etc.), or defined in other appropriate ways. Preferably, the desired stiffness distribution is determined by the ECU as a factor in determining the desired state of the vehicle suspension system, but it can also be determined by other appropriate systems. Determine the ideal stiffness distribution in order to affect (e.g., maintain, achieve, etc.) the relevant parameters of the suspension system; for example, determine (e.g., select, calculate) the desired stiffness distribution in order to maintain the height and / or flatness of the vehicle during loading (e.g., to prevent falling, by raising and / or strengthening the spring to support the heavier part of the spring load relative to other springs). Preferably, module S132 is executed in real time during vehicle operation (e.g., loading, driving, etc.), but additionally or alternatively, it can also be executed asynchronously periodically (e.g., every minute, every 15 seconds, etc.) based on a triggering event (e.g., an additional portion of the load is added to the cargo hold), or executed with any other suitable time characteristics.

[0095] Module S140 includes: converting the existing state of the vehicle suspension system to the desired state, which is used to achieve the ideal vehicle load distribution and / or arrangement. Preferably, module S140 is executed immediately after module S130 and in response to module S130, but additionally or selectively, it can also be executed at any other suitable time in response to any other suitable event (such as a trigger event, user input, etc.).

[0096] Module S140 includes module S141, which includes: determining a load instruction set. Module S141 is used to generate a set of instructions that describe how to modify the load to achieve a desired state of the suspension system (e.g., corresponding to a desired load distribution, a desired stiffness distribution, etc.). In one variant, module S141 is based on a desired load arrangement. For example, the loading instruction set includes verbal instructions that instruct a user to rearrange the vehicle load to achieve the desired load arrangement. Preferably, the S141 module is executed at the ECU, but additionally or alternatively, it can also be executed by any other suitable computing system.

[0097] Module S140 includes module S142, which includes: providing a loading instruction set for a vehicle user. The function of module S142 is to provide the user with the instruction set determined by module S141, so that the user can take actions according to the instruction set to achieve the desired state of the suspension system.

[0098] In one embodiment, modules S141 and S142 include generating an instruction set at an ECU and transmitting the instruction set to a user's mobile device. In another embodiment, modules S141 and S142 receive pressure measurements from an ECU in a processing system (e.g., a mobile device, a vehicle computing system, a remote computing system), generate an instruction set in the processing system, and transmit the instruction set to the user (e.g., at a display screen or interface of the processing system, on a mobile device associated with the user, etc.). However, modules S141 and S142 may also be performed in other suitable ways.

[0099] Module S140 includes module S143, which includes: automatically controlling a fluid spring group at a plurality of drive points based on a desired stiffness distribution, wherein controlling the fluid spring group includes setting a stiffness value of a fluid spring associated with each drive point. Preferably, the drive point is a physical location on the vehicle where a fluid suspension element (e.g., a fluid spring) applies force to an axle and a chassis to provide suspension of the vehicle, but the drive point may also be determined in other suitable ways. The function of module S143 is to directly adjust the pressure at the fluid spring (e.g., each individual fluid spring) to control the height and / or stiffness of the suspension system at each drive point. Module S143 can be executed (e.g., simultaneously, in parallel) with measuring the existing state of the suspension system and / or loading and unloading of the vehicle at a high frequency (e.g., once every 500 milliseconds), a low frequency (e.g., once per minute), an adjustable periodic frequency, or with any other suitable timing characteristics. In another variant, module S143 can be executed and a user instruction is received, and module S143 can be executed again according to the user instruction. Preferably, module S143 is executed by the ECU, but additionally or alternatively, it may also be executed by any other suitable computing system (e.g., a native application executed on a user's mobile device). In one specific example, module S143 includes: compressing a fluid, and then pumping the compressed fluid into a fluid spring along a pressurized fluid line, thereby increasing the pressure in the fluid spring, thereby increasing the stiffness of the fluid spring. In this specific example, module S143 includes: obtaining a set pressure point through a closed-loop control mechanism (e.g., the pressure measured in the fluid spring is the input to the control loop).

[0100] In a specific example, module S143 includes: driving the fluid spring group in response to the arrangement of at least one of the first and second load parts in the cargo hold, wherein driving the group of fluid springs minimizes the angle difference between a vector perpendicular to the bottom of the cargo hold and a gravity vector (e.g., making the cargo hold horizontal).

[0101] In another specific example, module S143 includes: automatically controlling the fluid spring group in response to terrain features predicted along the vehicle route (e.g., determined in module S112). In this example, module S143 includes: setting a first stiffness value for a first subset of a plurality of driving points on a first side of the vehicle, and setting a second stiffness value for a second subset of driving points on a second side opposite the first side (e.g., including predicted terrain features of a banked turn).

[0102] The implementation method includes a module S150, which includes: generating feedback for a user during loading. The function of module S150 is to inform an individual (e.g., a user) loading the vehicle of the instantaneous state of the vehicle load distribution so that the individual can load the vehicle in real time (e.g., substantially real time) according to the desired load distribution. Preferably, the feedback is generated based on the output of modules S120 and / or S130 (e.g., the state of the suspension system and the associated load arrangement in the vehicle), but additionally or alternatively, the feedback can also be generated based on vehicle condition parameters, a set of loading instructions (e.g., determined by module S141) and / or any other suitable basis. Preferably, the feedback is generated by the ECU, but additionally or alternatively, it can also be generated by any other suitable computing system. Preferably, the feedback is displayed to the user (e.g., on a graphical user interface) in real time or near real time during the operation of the vehicle (e.g., loading). For example, module S150 includes displaying a graphical representation of the vehicle and the load distribution in the vehicle, and highlighting the portion of the load in the vehicle that does not meet the set of loading criteria (e.g., exceeding the maximum weight of the axle located at the highlighted portion of the load). However, additionally or alternatively, module S150 may also generate feedback in any other suitable manner.

[0103] In one variation, module S150 includes providing a notification to a vehicle user. The notification includes any suitable information related to the vehicle load, including: a fraction of the vehicle load supported by each fluid spring of the fluid spring assembly, an indication that the load is not properly arranged, and repair instructions (e.g., Fig. 6A As shown), vehicle overload warning (such as Figure 6B), and any other suitable load-related data or information. In a related variation, module S150 further includes: presenting the notification graphically on a device associated with the user; receiving input from the user on the device; and actuating the fluid spring group based on the input. Additionally or alternatively, module S150 may include: receiving input from the user on an interface (e.g., an overlay switch, a dashboard console, etc.), and actuating the suspension system (or stopping actuation) in response to the input on the interface.

[0104] In another variation, module S150 includes: substantially real-time monitoring of pressure values ​​during vehicle loading, determining a real-time load arrangement, and comparing the real-time load arrangement with a second load arrangement. In this variation, module S150 also includes providing a notification to a user based on the comparison. In one example, the notification instructs the user to comply with the loading instruction set to a certain extent. In another example, when a load is detected that exceeds the maximum load that the main suspension and / or the main suspension and the lifting axle combination can withstand, module S150 can provide an overload alarm (e.g., via a dashboard indicator).

[0105] The implementation method includes a module S160, which includes: automatically deploying a lifting axle (such as a descent axle) using a fluid suspension system when a deployment criterion is met. Module S160 is used to increase the number of axles that bear the vehicle load and / or increase the load borne by the lifting axle. The deployment criterion includes any conditions indicating that additional load-bearing axles are required, such as: the total load weight exceeds a threshold, the number of axles allowed corresponding to the vehicle's geographic location exceeds the existing number of deployed axles, and any other suitable conditions. In a specific example, module S160 includes increasing fluid pressure in one or more fluid-driven jacks (e.g., using a manifold controlled by an ECU) that drives the lifting axle away from the vehicle chassis and into contact with the ground, and continuing to increase fluid pressure until the lifting axle carries the desired vehicle load weight (e.g., in combination with the measured pressure of the fluid-driven jack and other suspension elements). In another specific example, module S160 includes using a first fluid-driven suspension element (or group of such elements) to deploy the axle (e.g., move the axle out of contact with the ground), and using a second fluid-driven suspension element (or group of such elements) to adjust the load carried by the lift axle (e.g., increase fluid pressure until the axle carries the desired vehicle load weight).

[0106] In one variation of module S160, the deployment criteria includes a desired stiffness distribution that includes a stiffness value exceeding a threshold value (eg, corresponding to one of the fluid springs).

[0107] The implementation method includes a module S170, which includes: automatically retracting the lifting axle (such as the lowering axle) using the fluid suspension system when a retraction criterion is met. Module S170 is used to reduce the number of load-bearing axles and / or reduce the load borne by the lifting axle. The retraction criteria include any conditions indicating that fewer load-bearing axles are needed, such as: the total load weight is below a threshold, the existing number of deployed axles exceeds the number of axles allowed corresponding to the vehicle's geographic location, additional fuel economy is required and no additional load is required, weather conditions indicating a need for increased traction (such as at the drive axle), and any other suitable conditions. In a specific example, module S160 includes reducing fluid pressure in one or more fluid-driven jacks (e.g., using a manifold controlled by an ECU) that drives the lifting axle out of contact with the ground and toward the vehicle chassis, and continuing to reduce fluid pressure until the lifting axle carries the desired vehicle load weight (e.g., in combination with the measured pressure of the fluid-driven jack and other suspension elements). In another specific example, module S170 includes using a first fluid-driven suspension element (or group of such elements) to retract the axle (e.g., move the axle away from contact with the ground) and using a second fluid-driven suspension element (or group of such elements) to adjust the load carried by the lift axle (e.g., reduce fluid pressure until the axle carries the desired vehicle load weight).

[0108] In a variation of module S170, the retraction criteria include a planned path of the vehicle including a turning angle exceeding a threshold value. In this variation, automatically retracting the lowering axis is performed in a time period approaching or before the vehicle turns.

[0109] Modules S160 and S170 may be executed synchronously (e.g., alternately increasing and decreasing the pressure at the lift axle) to maintain the desired difference in load between the primary suspension (e.g., the suspension of a non-liftable axle, the suspension of a drive axle, etc.) and the secondary suspension (e.g., the suspension of an extendable / retractable axle). Figure 7 As shown, the pressure at a lift axle suspension element (such as an air spring) can be adjusted over time, which in turn is associated with the dynamic loading / unloading of the vehicle (ie, the load can vary as a function of time). Figure 7 As shown, modules S160 and S170 may be based on the primary suspension load exceeding and / or falling below a threshold pressure (eg, a deployment threshold).

[0110] Modules S160 and S170 may be executed in conjunction with lift axis control to implement single lift axis control, multiple lift axis control and / or main suspension height control.

[0111] The implementation method also includes a module S180, which includes: automatically adjusting fluid pressure in at least one tire of the vehicle using a fluid suspension system based on the front and rear data. In an example, module S180 includes managing tire pressure substantially as described in the text of U.S. patent application Ser. No. 15 / 805,015 filed on Nov. 6, 2017, and incorporated herein by reference in its entirety. However, module S180 also includes controlling pressure in one or more tires of the vehicle in other suitable ways.

[0112] 4. Examples

[0113] like Figure 8 As shown, a first specific embodiment of method 100 includes: S111, determining a set of loading standards; S121, sampling the fluid pressure of the fluid spring group at the manifold of the fluid suspension system during vehicle loading; S122, determining a first load arrangement based on the set of fluid pressures, wherein the first load arrangement includes a coordinate mapping between a first discrete portion of the vehicle load and a first position in the vehicle cargo compartment; S131, determining a second load arrangement based on the loading standards, wherein the second load arrangement includes a second coordinate mapping between a second discrete portion of the vehicle load and a second position in the vehicle cargo compartment; S141, determining a loading instruction set based on the second load arrangement; and S142, providing the loading instruction set to a vehicle user.

[0114] like Fig. 9 As shown, a second specific embodiment of method 100 includes: S121, sampling the fluid pressure of a fluid spring group at a manifold of a fluid suspension system, wherein the fluid spring group supports a vehicle load at multiple driving points; S123, determining an existing stiffness distribution based on the fluid pressure group, the existing stiffness distribution including a stiffness value associated with each fluid spring; S112, determining a front-rear related data set substantially in real time during vehicle operation; S132, determining a desired stiffness distribution based on the front-rear related data set; and S143, automatically controlling the fluid spring group at the driving point based on the desired stiffness distribution, wherein controlling the fluid spring group includes setting a stiffness value of the fluid spring associated with each driving point.

[0115] Preferably, another embodiment implements the above method in a computer readable medium storing readable instructions. Preferably, the instructions are executed by a computer executable component integrated with a fluid suspension control unit. The fluid suspension control unit may include a pressure control system, a manifold, and any other suitable components. The computer readable medium may be stored on any suitable readable medium, such as a memory (RAM), a read-only memory (ROM), a flash memory, an electrically erasable read-only memory (EEPROM), an optical device (CD or DVD), a hard drive, a floppy disk drive, or any suitable device. Preferably, the computer executable component is a processor, but additionally or additionally, the instructions may be executed by any suitable dedicated hardware device.

[0116] The above description is omitted for brevity, but the preferred embodiment includes every combination and permutation of the various system components and the various method processes, wherein the method processes can be performed sequentially or simultaneously in any suitable order.

[0117] Based on the foregoing detailed description, the accompanying drawings and the appended claims, those skilled in the art may modify and alter the preferred embodiments of the present invention without departing from the scope of the following claims.

Claims

1. A method of analyzing and managing vehicle loads carried by a vehicle having a fluid suspension system, characterized in that The method comprises: - sampling a fluid pressure corresponding to a set of fluid springs of a fluid suspension system at a manifold of the fluid suspension system, wherein the set of fluid springs supports the vehicle load at a plurality of actuation points; - determining an existing stiffness profile based on the fluid pressure, the existing stiffness profile comprising stiffness values ​​associated with each fluid spring in the set of fluid springs; - Determining context-dependent data sets substantially in real time during vehicle operation; - determining a desired stiffness distribution based on the anteroposterior correlation data set; - automatically controlling a set of fluid springs at a plurality of driving points based on the desired stiffness profile, wherein controlling the set of fluid springs comprises setting a stiffness value of a fluid spring associated with each of the plurality of driving points; wherein the context-dependent dataset includes predicted terrain features, and the context-dependent dataset is determined based on a planned route of the vehicle and terrain features associated with the planned route; The predicted terrain feature includes a sloped road, and wherein automatically controlling the fluid spring group includes: setting a first stiffness value for a first subset of multiple driving points on a first side of the vehicle, and setting a second stiffness value for a second subset of multiple driving points on a second side opposite to the first side of the vehicle to actively control the vehicle's posture by controlling the stiffness of the fluid suspension system, the posture including the roll angle.

2. A method of analyzing and managing vehicle loads carried by a vehicle having a fluid suspension system, characterized in that The method comprises: - sampling a fluid pressure corresponding to a set of fluid springs of a fluid suspension system at a manifold of the fluid suspension system, wherein the set of fluid springs supports the vehicle load at a plurality of actuation points; - determining an existing stiffness profile based on the fluid pressure, the existing stiffness profile comprising stiffness values ​​associated with each fluid spring in the set of fluid springs; - Determining context-dependent data sets substantially in real time during vehicle operation; - determining a desired stiffness distribution based on the anteroposterior correlation data set; - automatically controlling a set of fluid springs at a plurality of driving points based on the desired stiffness profile, wherein controlling the set of fluid springs comprises setting a stiffness value of a fluid spring associated with each of the plurality of driving points; wherein the fore-aft related data set includes an indication that the vehicle is loaded, and wherein automatically controlling the fluid spring assembly includes maintaining a base surface of the vehicle cargo hold substantially perpendicular to a gravity vector during loading, wherein the vehicle load includes discrete load portions.

3. A method of analyzing and managing vehicle loads carried by a vehicle having a fluid suspension system, characterized in that The method comprises: - sampling a fluid pressure corresponding to a set of fluid springs of a fluid suspension system at a manifold of the fluid suspension system, wherein the set of fluid springs supports the vehicle load at a plurality of actuation points; - determining an existing stiffness profile based on the fluid pressure, the existing stiffness profile comprising stiffness values ​​associated with each fluid spring in the set of fluid springs; - Determining context-dependent data sets substantially in real time during vehicle operation; - determining a desired stiffness distribution based on the anteroposterior correlation data set; - automatically controlling a set of fluid springs at a plurality of driving points based on the desired stiffness profile, wherein controlling the set of fluid springs comprises setting a stiffness value of a fluid spring associated with each of the plurality of driving points; - using the fluid suspension system to automatically change the position of the lifting shaft, including at least one of the following: automatically deploying the lifting shaft when the deployment criteria are met; or automatically retracting the lifting shaft when the retraction criteria are met; The deployment criteria include a planned route for the vehicle, the route including travel of the vehicle in a geographic area associated with regulatory rules, the regulatory rules including weight limits for each axle; The retraction criteria include a planned path of the vehicle including a turn exceeding a turn angle threshold; wherein automatically retracting the lifting axle is performed within a time period approaching or prior to the vehicle turning.

4. The method according to claim 3, characterized in that The deployment criteria includes the desired stiffness profile including a stiffness value exceeding a stiffness threshold at a fluid spring of the set of fluid springs.

5. The method according to claim 3, characterized in that: The method also includes automatically adjusting fluid pressure in at least one tire of the vehicle using the fluid suspension system based on the fore-aft data.

6. The method according to claim 5, characterized in that The fore-aft data includes the total weight of the vehicle load.

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