CN-121989913-A - Amphibious vehicle control method based on stability and economic collaborative optimization

CN121989913ACN 121989913 ACN121989913 ACN 121989913ACN-121989913-A

Abstract

The invention is suitable for the technical field of vehicle control, and provides a control method of an amphibious vehicle based on stable and economic collaborative optimization, which solves the additional moment required for maintaining the stable posture of the vehicle through real-time working condition identification and adaptive model predictive control, and calculates the stability power requirement by combining multi-objective optimization allocation; the method comprises the steps of superposing the stability power and the longitudinal propulsion power to obtain the total power demand of the system, constructing an energy management model of the hybrid power system based on the total power demand, utilizing a self-adaptive equivalent factor iteration update strategy based on a neural network to realize overall optimization distribution of the power of an engine and the power of a battery, converting an optimized power instruction into torque and distributing the torque to a corresponding driving unit. The full scene stability constraint depth is coupled to the energy management closed loop, so that the problem of stability and economy optimization disjoint is solved, and the energy economy of the whole amphibious vehicle is improved on the premise of ensuring the full-working-condition running safety and the stable posture of the amphibious vehicle.

Inventors

ZHU ZHONGWEN
DONG QICHEN
LI CHENG
QIU XIN
SHI ZHENGPENG
Pan Dieshan

Assignees

合肥工业大学

Dates

Publication Date: 20260508
Application Date: 20260211

Claims (9)

1. The control method of the amphibious vehicle based on the cooperative optimization of stability and economy is characterized by comprising the following steps: S1, motor power distribution under a stability target is carried out, namely, a self-adaptive model prediction controller is designed based on the real-time state of a vehicle and the operation working condition identified through a clustering algorithm, and additional moment meeting the stability of the posture of the vehicle is solved; s2, a total power demand integration step, namely superposing the motor power maintaining stability and the longitudinal propulsion power of the vehicle obtained through a dynamics model to obtain the total power demand of the system; S3, an adaptive energy management optimization step, namely constructing an energy management optimization model comprising an engine and a power battery based on the total power demand, adopting an equivalent factor iteration updating method based on a neural network, and optimizing and distributing the output power of the engine and the power battery through an adaptive equivalent energy consumption minimum strategy to realize the minimization of the equivalent energy consumption of the system; and S4, the power source output execution step of converting the output power of the engine and the battery after the optimization and distribution into torque and distributing the torque to the corresponding driving units according to the current working mode.
2. A control method for an amphibious vehicle based on synergistic optimization of stability and economy as claimed in claim 1, further comprising, before step S1: And constructing a multi-mode dynamics model covering land and water based on the amphibious vehicle parameter model, wherein the land reference model is a linear two-degree-of-freedom model with state quantity comprising yaw rate and centroid slip angle, and the water reference model is a three-degree-of-freedom model for controlling the water surface posture.
3. The amphibious vehicle control method based on the cooperative optimization of stability and economy according to claim 2, wherein the operation conditions identified by the clustering algorithm in step S1 are specifically: The K-Means clustering algorithm is utilized, the vehicle speed, the acceleration and the working condition duration which are acquired in real time are used as input characteristics, and the working condition types including land straight-road running, a wasaki off-road working condition, a muddy wet working condition, stable water sailing, water wind wave disturbance sailing and up-down beach ship are identified in real time.
4. The amphibious vehicle control method based on cooperative optimization of stability and economy according to claim 1, wherein the design adaptive model predictive controller in step S1 solves additional moment, and specifically comprises: Establishing a multi-target fusion prediction model, wherein for a land working condition, the core state of the model is a centroid slip angle and a yaw rate, for a water working condition, the core state of the model is a roll angle, a pitch angle and a yaw angle, and establishing a stability dominant objective function: ; Wherein: As a state vector of the state vector, For an ideal reference trajectory, deltau is the control quantity change rate, Q/R is the weighting matrix, To predict the time domain.
5. The control method of the amphibious vehicle based on the cooperative optimization of stability and economy according to claim 1, wherein the multi-objective coordination with the stability objective and the economy objective in the step S1 is specifically: when the vehicle is running on land, the stability target is the minimum sum of the tire load rates, and the target function is as follows: ; In the middle of The torque is output for the in-wheel motor, For the road surface adhesion coefficient, For the vertical loading of the wheel end, An effective rolling radius for the wheel; When the vehicle runs on water, the stability target is that the maximum value of the water thrust load rate is minimized, and the objective function is that: ; in the formula, Is the actual output thrust of the 1 st power plant, The maximum available thrust of the device under the current rotating speed and water flow working condition; The economic goal is to minimize the motor power loss, and the objective function is: ; In the middle of Is the maximum power of the motor.
6. The amphibious vehicle control method based on cooperative optimization of stability and economy according to claim 1, wherein the power balance equation for the total power demand in step S2 is: ; in the formula, For the output power of the engine, For the output power of the battery, Is the total power demand.
7. The amphibious vehicle control method based on cooperative optimization of stability and economy according to claim 1, wherein the adaptive equivalent energy consumption minimization strategy in step S3 is based on the objective optimization problem of minimizing the equivalent fuel consumption of the full stroke of the system: ; in the formula, In order to achieve a fuel consumption of the engine, Equivalent fuel consumption for electric energy; wherein the actual fuel consumption ; In the formula, For the low heating value of the fuel, For the purpose of the working efficiency of the engine, The power generated when the engine is running.
8. The amphibious vehicle control method based on the cooperative optimization of stability and economy according to claim 1, wherein the neural network-based equivalent factor iterative updating method in the step S3 comprises an offline learning stage and an online self-adaptive updating stage; the offline learning stage solves a global optimal solution by adopting the Pontrisia minimum value principle aiming at given typical amphibious working conditions, and constructs a system Hamiltonian: ; in the formula, Synergistic variables for battery state of charge And an equivalent factor updating mechanism based on a prospective equivalent energy consumption minimum strategy is introduced to carry out iterative optimization solution by combining a working condition demand prediction result in the online self-adaptive updating stage.
9. A control method for an amphibious vehicle based on synergistic optimization of stability and economy according to claim 1, characterized in that in step S4 the said allocation to the respective driving units according to the current operating mode is in particular: In the land working mode, torque is distributed to four hub motors and driving motors, and in the water working mode, torque is distributed to two jet pump motors.

Description

Amphibious vehicle control method based on stability and economic collaborative optimization Technical Field The invention belongs to the technical field of vehicle control, and particularly relates to a control method of an amphibious vehicle based on stability and economic collaborative optimization. Background The amphibious vehicle is used as special equipment with double running capability of land and water surface, and has irreplaceable important value in the fields of emergency rescue, military reconnaissance, scientific investigation and the like. With the continuous rise of requirements for high mobility, high reliability and intelligent level of equipment, the dynamics control and energy management of amphibious vehicles become the key to research. At present, researches on the vehicles mainly focus on two relatively independent directions, namely stability control based on vehicle dynamics, which aims at maintaining the running posture of the vehicles under complex road surfaces or disturbance water areas through driving torque distribution or propeller coordination, and energy management strategies based on an optimization theory, which aims at reducing the energy consumption of the whole vehicle through reasonably distributing the output power of an engine and a battery. However, in actual operation of the vehicle, the control actions required to maintain stability directly consume power, and this portion of the stability power demand, together with the conventional longitudinal propulsion power demand, constitutes the actual load of the whole vehicle. How to combine the two organically and realize the optimal energy efficiency of the system on the premise of ensuring the running safety under all working conditions is a core difficult problem to be solved in the field. Although the prior art considers the all-condition mode, it is mostly essential to consider the stability control and energy management of the vehicle as two separate, tandem links. The power requirements on which the energy management strategy is based do not fully account for the real-time, dynamic additional power consumption that is generated to maintain vehicle lateral, heading and attitude stability. Therefore, the existing scheme is difficult to realize global cooperative optimization of vehicle running stability and economy under the key scenes of complex and changeable land rugged road surfaces, water storm disturbance, water-land transition and the like. The energy distribution results may be either insufficient in stability assurance or too costly in terms of economic sacrifice due to an inability to accurately match the actual total power load including stability requirements. Disclosure of Invention The invention aims to provide a control method of an amphibious vehicle based on stable and economic collaborative optimization, which aims to solve the problems in the background technology. The invention is realized in such a way, and an amphibious vehicle control method based on stability and economic collaborative optimization is characterized in that an integrated control framework integrating stability constraint and energy management is constructed. The method sequentially executes the following key steps: S1, motor power distribution under a stability target, namely collecting vehicle state and working condition identification information in real time through a vehicle-mounted sensor network, and accurately identifying a specific running mode of the vehicle at present by utilizing a clustering algorithm. And calling a preset differential vehicle dynamics reference model (a 2-DOF model is adopted on land and a 3-DOF model is adopted on water) to generate a stability control target based on the identified working condition. And designing an adaptive model prediction controller, wherein the controller synthesizes the real-time vehicle state and the target value, and solves the real-time vehicle state and the target value on line to obtain additional moment (yaw moment on land and yaw, pitch and roll moment on water) required for maintaining the stable vehicle posture. Finally, in the lower control, the multi-target coordination torque distribution is carried out on each driving unit (hub motor and jet pump motor) by combining the stability targets such as the minimum tire load rate, the balanced thrust load rate and the like and the economic targets with the minimum motor power loss, and the consumed motor power for maintaining the stability is calculated. S2, integrating total power demands, namely calculating the core propulsion power for driving the vehicle to advance according to the longitudinal movement demands of the vehicle while finishing the stability moment distribution. And (3) superposing the stability power and the propulsion power obtained in the step (S1) so as to obtain the total power demand of the system at the current moment. The step uniformly quantizes the original independent stable energy cons