CN116729356A

CN116729356A - New energy automobile control system and method based on Internet of things technology

Info

Publication number: CN116729356A
Application number: CN202310650675.XA
Authority: CN
Inventors: 刘海清; 常静; 刘伟; 陈泳宏
Original assignee: Shenzhen Zest Technology Co ltd
Current assignee: Shenzhen Zest Technology Co ltd
Priority date: 2023-06-02
Filing date: 2023-06-02
Publication date: 2023-09-12
Anticipated expiration: 2043-06-02
Also published as: CN116729356B

Abstract

According to the historical working data of different fuel power vehicles, fuel cell power vehicles and hybrid power vehicles, large data analysis technology and a neural network are utilized to establish each working model of different power vehicles, then feature extraction and integration are carried out on each working model to generate an initial power switching control model, then related data of a first new energy vehicle are combined to obtain a first power switching control model, and finally a first power switching control scheme for carrying out power switching on the first new energy vehicle is generated according to first environment data, first vehicle state data and the first power switching control model, so that power switching on the hybrid power vehicle can be achieved, accurate power switching can be carried out according to the environment data and the vehicle state, vehicle safety is guaranteed, and user experience is improved.

Description

New energy automobile control system and method based on Internet of things technology

Technical Field

The invention relates to the technical field of the Internet of things, in particular to a new energy automobile control system and method based on the Internet of things technology.

Background

With the development of battery technology, communication technology, image recognition technology, computer hardware technology, new material technology and the like, and the improvement of environmental awareness, new energy automobiles carrying large-capacity batteries and integrating automation technology and internet of things technology gradually become a mainstream trend in automobile markets due to energy conservation and emission reduction and energy price advantages compared with pure fuel automobiles.

The driving scheme of the new energy automobile is a traditional driving method of removing the tire from the fuel automobile, and the driving control aspect of the new energy automobile is still behind, for example, compared with the simplicity of the judging relation between the number of mileage of the fuel automobile and the fuel consumption, the driving distance of the residual electric quantity (or the residual electric quantity and the fuel) of the new energy automobile (especially the new energy automobile with mixed power) is difficult to accurately judge; there is also a disadvantage in how to accurately manage a power system for a hybrid vehicle. The existing control system of the new energy automobile has the defects of accuracy, intellectualization and the like in the control of the new energy automobile.

Disclosure of Invention

The invention is based on the problems, and provides a new energy automobile control system and method based on the Internet of things technology.

In view of this, an aspect of the present invention proposes a new energy automobile control system based on the internet of things technology, including: the system comprises a cloud server, an Internet of things server, a central control unit, a sensor group, a communication unit, a power switching unit, a fuel engine subsystem, a motor subsystem, an electron storage subsystem and a fuel cell subsystem;

the cloud server is configured to:

acquiring first historical working data of various fuel automobiles, second historical working data of various hybrid electric automobiles and third historical working data of various fuel cell power automobiles;

generating a first working model according to the first historical working data, generating a second working model according to the second historical working data, generating a third working model according to the third historical working data, and generating an initial power switching control model according to the first working model, the second working model and the third working model;

acquiring first production data and first test data of each minimum unit of a first new energy automobile, and acquiring whole automobile test data and whole automobile assembly data of the first new energy automobile;

generating a first power switching control model of the first new energy automobile according to the first production data, the first test data, the whole vehicle assembly data and the initial power switching control model; the first power switching control model is sent to the Internet of things server currently connected with the first new energy automobile;

The central control unit is configured to:

controlling the sensor group to acquire first environment data and first vehicle state data of the environment where the first new energy automobile is located;

transmitting the first environmental data and the first vehicle state data to the internet of things server through the communication unit;

the internet of things server is configured to: and generating a first power switching control scheme for switching power of the first new energy automobile according to the first environment data, the first vehicle state data and the first power switching control model.

Optionally, in the step of generating the first power switching control model of the first new energy automobile according to the first working data, the first production data, the first test data, the whole vehicle assembly data and the initial power switching control model, the cloud server is specifically configured to:

extracting second test data of the fuel engine subsystem, third test data of the motor subsystem, fourth test data of the electron storage subsystem and fifth test data of the fuel battery subsystem from the whole vehicle test data;

And adjusting the initial power switching control model according to the first working data, the first production data, the first test data, the second test data, the third test data, the fourth test data, the fifth test data and the whole vehicle assembly data to obtain the first power switching control model.

Optionally, in the step of controlling the sensor group to acquire first environmental data and first vehicle state data of an environment in which the first new energy automobile is located, the central control unit is configured to:

grouping the sensor groups to obtain a plurality of sensor subgroups;

acquiring first current position data of the first new energy automobile;

and determining one or more corresponding first sensor subgroups from the plurality of sensor subgroups according to the first current position data, and triggering the first sensor subgroups to acquire the first environment data and the first vehicle state data.

Optionally, the step of generating a first power switching control scheme for switching power of the first new energy automobile according to the first environmental data, the first vehicle state data and the first power switching control model, and the internet of things server is specifically configured to:

Extracting road data, temperature data, wind data, air pressure data and air composition data from the first environmental data;

extracting motor state data, storage battery electric quantity data, engine state data, fuel oil data, air supply device data and fuel cell data from the first vehicle state data;

and generating the first power switching control scheme according to the road data, the temperature data, the wind power data, the air pressure data, the air component data, the motor data, the storage battery electric quantity data, the engine state data, the fuel oil data, the air supply device data, the fuel cell data and the first power switching control model.

Optionally, the internet of things server is configured to:

determining whether the first new energy automobile needs power system switching;

if the power system is required to be switched, controlling the first new energy automobile to perform power switching operation according to the first power switching control scheme;

when the first new energy automobile does not need to be subjected to power system switching, acquiring first navigation data and second current position data of the first new energy automobile;

Predicting first road section environment data of a first road section to be passed by the first new energy automobile in a preset first time according to the first navigation data and the second current position data;

predicting a first power demand of the first new energy automobile when the first new energy automobile passes through the first road section according to the first road section environment data;

determining whether a power system of the first new energy automobile can be met according to the first power demand and a first power matching model of the first new energy automobile;

when the power system of the first new energy automobile cannot meet the first power requirement, the vehicle state of the first new energy automobile is adjusted in advance.

The invention provides a new energy automobile control method based on the internet of things technology, which is applied to a new energy automobile control system based on the internet of things technology, wherein the new energy automobile control system based on the internet of things technology comprises a cloud server, an internet of things server, a central control unit, a sensor group, a communication unit, a power switching unit, a fuel engine subsystem, a motor subsystem, an electron storage subsystem and a fuel cell subsystem, and the new energy automobile control method based on the internet of things technology comprises the following steps:

The cloud server acquires first historical working data of various fuel automobiles, second historical working data of various hybrid electric vehicles and third historical working data of various fuel cell power automobiles;

the cloud server generates a first working model according to the first historical working data, generates a second working model according to the second historical working data, generates a third working model according to the third historical working data, and generates an initial power switching control model according to the first working model, the second working model and the third working model;

the cloud server acquires first production data and first test data of each minimum unit of a first new energy automobile, and acquires whole vehicle test data and whole vehicle assembly data of the first new energy automobile;

the cloud server generates a first power switching control model of the first new energy automobile according to the first production data, the first test data, the whole vehicle assembly data and the initial power switching control model; the first power switching control model is sent to the Internet of things server currently connected with the first new energy automobile;

The central control unit controls the sensor group to acquire first environment data and first vehicle state data of the environment where the first new energy automobile is located;

the central control unit sends the first environment data and the first vehicle state data to the internet of things server through the communication unit;

and the Internet of things server generates a first power switching control scheme for performing power switching on the first new energy automobile according to the first environment data, the first vehicle state data and the first power switching control model.

Optionally, the step of generating, by the cloud server, the first power switching control model of the first new energy automobile according to the first working data, the first production data, the first test data, the whole vehicle assembly data and the initial power switching control model includes:

Optionally, the step of controlling the sensor group to acquire the first environmental data and the first vehicle state data of the environment where the first new energy automobile is located by the central control unit includes:

grouping the sensor groups to obtain a plurality of sensor subgroups;

acquiring first current position data of the first new energy automobile;

Optionally, the step of generating, by the internet of things server, a first power switching control scheme for performing power switching on the first new energy automobile according to the first environmental data, the first vehicle state data and the first power switching control model includes:

Optionally, the method further comprises:

According to the technical scheme, the new energy automobile control method based on the Internet of things technology is characterized in that firstly, according to historical working data of different fuel power (namely internal combustion engine power) automobiles, fuel cell power automobiles and hybrid power automobiles, a big data analysis technology and a neural network are utilized to build each working model of the different power automobiles, then, feature extraction and integration are carried out on each working model to generate an initial power switching control model, then, related data of a first new energy automobile is combined to obtain a first power switching control model, and finally, according to first environment data, first vehicle state data and the first power switching control model, a first power switching control scheme for carrying out power switching on the first new energy automobile is generated, so that power switching on the hybrid power automobile can be realized, accurate power switching can be carried out according to environment data and vehicle states, vehicle safety is guaranteed, and user experience is improved.

Drawings

FIG. 1 is a schematic block diagram of a new energy automobile control system based on the Internet of things technology according to one embodiment of the present application;

fig. 2 is a flowchart of a new energy automobile control method based on the internet of things technology according to an embodiment of the present application.

Detailed Description

In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced otherwise than as described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.

The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The following describes a new energy automobile control system and method based on the internet of things technology according to some embodiments of the present application with reference to fig. 1 to 2.

As shown in fig. 1, an embodiment of the present application provides a new energy automobile control system based on the internet of things technology, including: the system comprises a cloud server, an Internet of things server, a central control unit, a sensor group, a communication unit, a power switching unit, a fuel engine subsystem, a motor subsystem, an electron storage subsystem and a fuel cell subsystem;

the cloud server is configured to:

acquiring first production data and first test data of each minimum unit (such as a minimum assembly unit, a minimum part, a minimum component, a minimum structure and the like) of a first new energy automobile, and acquiring whole vehicle test data and whole vehicle assembly data of the first new energy automobile;

generating a first power switching control model of the first new energy automobile according to the first production data, the first test data, the whole vehicle assembly data and the initial power switching control model; the method comprises the steps of obtaining position information of a first new energy automobile by communicating with the first new energy automobile, and determining an Internet of things server to which the first new energy automobile is currently connected according to the position information of the first new energy automobile; the first power switching control model is sent to the Internet of things server currently connected with the first new energy automobile;

The central control unit is configured to:

controlling the sensor group to acquire first environment data (including but not limited to environment control data, air composition data/pressure data, temperature data, humidity data, road surface data and the like) and first vehicle state data (including but not limited to engine output power, rotating speed, oil consumption, cylinder pressure, engine oil pressure, maximum power, maximum torque, fault data, coolant temperature, motor output power, battery power, charging times, air inlet temperature, exhaust temperature, vehicle speed, vehicle body quality, vehicle load, tire data, vehicle exterior shape/resistance data and the like) of the environment in which the first new energy automobile is located;

the internet of things server is configured to: and generating a first power switching control scheme (including but not limited to a power range which can be output by each power supply mode, the requirement of the current environment/the current vehicle condition on the power/the vehicle speed, the requirement on the safety of a power source, the power switching time, the power transition mode and the like) for switching the power of the first new energy automobile according to the first environment data, the first vehicle state data and the first power switching control model.

It will be appreciated that in embodiments of the present invention, the first/second/third operational model includes, but is not limited to, the following operational models or operational paradigms under conditions of different environments, different vehicle states, etc.: 1. working models/models of power systems (such as a fuel engine subsystem or a motor subsystem, an electronic storage system or a fuel cell subsystem, a power switching unit and the like, mainly comprising structures or components of an engine/motor, a transmission mechanism, a driving shaft, a storage battery and the like); 2. the control system (mainly comprises an engine control unit, a gearbox control unit, a brake system control unit and other parts which are responsible for coordinating the work of the systems and realizing the control of the vehicle); 3. the working model/paradigm of the chassis system (mainly comprising a frame, a suspension system, a steering system, a brake system and the like which are responsible for the movement of the automobile and provide the operability and the riding comfort during running); 4. working models/paradigms of auxiliary systems (mainly including air conditioning systems, navigation systems, safety systems, comfort systems, etc. parts for improving the ride experience and ease of use of the vehicle); 5. the central control unit (mainly used for controlling the matching and adjustment of a power system and a chassis system according to the change data of the position, the speed and the acceleration of the automobile in the running process and controlling the work of each part of the automobile according to the quality parameters of the automobile, the chassis structure, the contact data of tires and the ground, the stress of the automobile body and the load distribution data). The first/second/third working model is used for transmitting and converting power output by the engine to power, and finally driving force to the ground of the wheel pair comprehensively comprises the conventional working modes of the automobile in the complete working process from input to output, wherein all parts/systems are mutually matched, and the automobile is guaranteed to run efficiently, comfortably and safely. And extracting characteristic data about power demand prediction, power limit judgment, economic evaluation, power switching strategy, power smooth switching, power management control, fuel cell management, system control and the like according to the first/second/third working models, and combining deep learning technology to generate an initial power switching control model for performing power switching control on a new energy automobile (i.e. a vehicle integrating a fuel engine, a motor, a storage battery and a fuel cell) integrating a fuel engine subsystem, a motor subsystem, a storage electronic system and a fuel cell subsystem so as to realize switching of modes of fuel engine power supply, storage battery power supply and fuel cell power supply.

In some possible embodiments of the present invention, the cloud server may acquire related data (including, but not limited to, the first production data, the first test data, the whole vehicle assembly data, etc.) of the first new energy automobile, establish a working model of the first new energy automobile, and then, according to a migration learning technology, combine the initial power switching control model to generate a first power switching control model of the first new energy automobile.

The working model of the first new energy automobile at least comprises the following components: an energy system working model comprising components such as a new energy battery pack, a fuel cell and the like; a working model of a motor driving system comprising a motor, a motor controller and other components; the working model of an energy management system (which is responsible for monitoring and managing the states of different energy sources, coordinating the coordination work of the energy sources and realizing the optimal energy utilization) comprises an energy control unit, a charging system and the like; the temperature of the motor, the electric control system, the battery pack and the like is controlled to ensure that the motor, the electric control system and the battery pack work in an optimal temperature range, and meanwhile, the waste heat is utilized to improve the working model of the thermal management system of the system; an operating model of an energy storage system comprising components such as a battery pack, a super capacitor and the like; a working model of a composite power system (improving the endurance and economy of the whole vehicle through the composite utilization of various power sources) comprising an internal combustion engine, a generator, a motor and the like; the energy generated during braking is recycled through the braking energy recycling system, so that a power supply is provided for a driving motor and other electric loads, and the energy utilization efficiency is improved; the working model of the power switching unit (intelligent coordination and scheduling are carried out on different power units and energy systems according to working conditions and road conditions, so that optimal power performance, economical efficiency and endurance are realized).

The initial power switching control model/the first power switching control model at least comprises the following functional modules:

and (3) power demand prediction: and predicting the power demand for a period of time in the future according to the environment data, the vehicle state data and the driving mode, and taking the power demand as a reference basis for switching decisions. And (3) SOC estimation: estimating the state SOC of the battery in real time to ensure that the battery cannot be excessively discharged in any power mode, and the service life of the battery is influenced; SOC estimation typically builds an equivalent circuit model based on battery voltage, current, temperature, etc.

And (3) judging power limitation: it is determined whether the internal combustion engine and the electric motor can each individually meet the demand or whether hybrid drive is required under the current vehicle speed and power demand conditions, which is also a constraint condition for switching control.

Economic evaluation: based on an accurate internal combustion engine and motor power consumption mapping model established by the cloud server, the fuel consumption rate or the electric energy consumption rate of the internal combustion engine and the motor under the current condition is estimated, and the most economical power mode is determined by combining the energy price.

Power switching strategy: and determining whether to adopt an internal combustion engine driving mode, an electric motor driving mode or a hybrid driving mode by adopting regular control, an optimized switching strategy and the like according to the comprehensive judgment of the conditions.

Smooth switching: based on a power regulation model which is constructed by a cloud server according to related data of a first new energy automobile and used for finely regulating and controlling power of an internal combustion engine and a motor, a switching execution strategy is formulated, smooth transition of driving force during power source switching is ensured, obvious shock feeling is not brought to passengers, and driving comfort is not influenced

And (3) power management control: according to the environment data and the vehicle state, switching control is performed between the storage battery and the fuel cell so as to determine whether the storage battery supplies power to the motor or the fuel cell supplies power to the motor and redundant electric quantity storage control is performed;

fuel cell management: the air intake, the working temperature, the output power and the like of the fuel cell are managed and controlled according to the environmental data and the vehicle state;

and (3) system control: the control signals are sent out according to a preset strategy to accurately control the gearbox, the internal combustion engine, the motor and other components, so that the smooth switching transition from the current power mode to the target power mode is realized, which is the key of the whole control system.

In some possible embodiments of the present invention, the specific steps of the first power switching control scheme configured to perform power switching on the first new energy automobile according to the first environmental data, the first vehicle state data and the first power switching control model by the internet of things server are as follows:

Collecting environmental data: environmental data including, but not limited to, road grade, road flatness, road pavement material, traffic conditions, temperature data, wind power data, air pressure data, air composition data, weather conditions, and the like are acquired, and the degree of influence of the traveling environment is determined.

Collecting vehicle state data: and acquiring data including, but not limited to, motor state data, storage battery power data, engine state data, fuel oil data, air supply device data, fuel cell data, battery SOC, super capacitor SOC and the like, and judging the working state of the whole vehicle power system.

Judging the working mode: and determining the current working mode of the vehicle, such as an electric mode, a generator mode or a hybrid power mode, according to the environment data and the vehicle state data.

Setting target parameters: and setting target parameters such as motor power, generator power, engine power and the like according to the determined working mode and control strategy.

The operation switching process comprises the following steps: and according to the current working mode and the target parameters, a first power switching control scheme comprising the transition time, the transition parameters and the like required by the switching process is obtained by adopting a first power switching control model operation.

And issuing a first power switching control scheme to the central control unit.

The central control unit coordinates and controls corresponding parts such as a motor, a generator, an engine and the like according to the first power switching control scheme, so that stable switching of the working mode is realized.

Feedback switching state: and the central control unit feeds back the actual parameters generated in the switching process to the Internet of things server and is used for monitoring the switching execution condition and updating the control model.

Repeating the steps: the Internet of things server and the central control unit continuously repeat the steps according to the environmental change and the new vehicle state, and intelligent switching and scheduling of the power system are realized.

The working process is based on a multi-element power system of the new energy automobile, environmental information and the state of the whole automobile are fully collected, an optimal power configuration scheme is calculated by using a power switching control model, and each electric control unit is finely coordinated to realize stable switching, so that the purposes of high-efficiency energy utilization and optimal driving performance are achieved.

It should be noted that in the embodiment of the invention, the internet of things servers are multiple, and the internet of things sensors with intelligent sensing capability and the new energy automobiles connected to the internet of vehicles are respectively managed and arranged on roads (or intelligent automobiles) in different areas or road sections, so that the sensors can be rapidly controlled to acquire data, process the data and timely control the new energy automobiles in real time.

According to the scheme provided by the embodiment of the invention, firstly, according to historical working data of different fuel power (namely internal combustion engine power) automobiles, fuel cell power automobiles and hybrid power automobiles, each working model of the different power automobiles is established by utilizing a big data analysis technology and a neural network, then, characteristic extraction and integration are carried out on each working model to generate an initial power switching control model, then, the first power switching control model is obtained by combining relevant data of a first new energy automobile, and finally, a first power switching control scheme for carrying out power switching on the first new energy automobile is generated according to first environment data, first vehicle state data and the first power switching control model, so that not only can power switching on the hybrid power automobile be realized, but also accurate power switching can be carried out according to the environment data and the vehicle state, the safety of the automobile is ensured, and the user experience is improved.

It should be noted that the block diagram of the new energy automobile control system based on the internet of things shown in fig. 1 is only schematic, and the number of the illustrated modules does not limit the protection scope of the present invention.

In some possible embodiments of the present invention, in the step of generating the first power switching control model of the first new energy automobile according to the first work data, the first production data, the first test data, the whole vehicle assembly data, and the initial power switching control model, the cloud server is specifically configured to:

It can be appreciated that, in order to quickly obtain the power switching control model conforming to the first new energy automobile, in this embodiment, the cloud server may further extract the second test data of the fuel engine subsystem, the third test data of the motor subsystem, the fourth test data of the electronic storage subsystem, and the fifth test data of the fuel cell subsystem according to the first working data, the first production data, the first test data, the whole vehicle assembly data, and the attribute data of each component (further, the second test data of the fuel engine subsystem, the third test data of the motor subsystem, the fourth test data of the electronic storage subsystem, and the fifth test data of the fuel cell subsystem, analyzing the historical working data/production data/test data/whole vehicle test data (or the second test data, the third test data, the fourth test data, the fifth test data)/whole vehicle assembly data and attribute data, the historical working data/production data/test data/whole vehicle test data (various power subsystem test data, storage battery system test data and the like)/whole vehicle assembly data and attribute data of the various hybrid vehicles, comprehensively comparing and analyzing the historical working data/production data/test data/whole vehicle assembly data and attribute data of the various fuel cell power vehicles, comparing the differences of the first novel energy vehicle and the various fuel cell power vehicles/the various hybrid vehicles/the various fuel cell power vehicles in terms of power systems, transmission structures, control strategies and the like, finding out commonalities and differences; determining a strategy (such as example migration, feature migration, relationship migration and the like) adopting migration learning according to the result of the difference analysis, and determining a migration path; according to the selected migration strategy, extracting useful knowledge in the data of the plurality of fuel-powered vehicles/the plurality of hybrid vehicles/the plurality of fuel-cell powered vehicles and migrating to the data of the first new energy vehicle to obtain a new data field for subsequently enhancing an initial power switching control model of the first new energy vehicle (such as migrating part of historical driving data for power demand prediction of the first new energy vehicle; migrating the plurality of fuel-powered vehicles/the plurality of hybrid vehicles/the plurality of fuel-cell powered vehicles, etc.). And training an initial power switching control model (comprising a rule-based control model or an optimization-based control model and the like) of the first new energy automobile by utilizing the new data field obtained by migration to obtain a basic power switching control model, verifying and testing the basic power switching control model obtained by migration, evaluating the effectiveness and adaptability of the basic power switching control model to the power switching control of the first new energy automobile, checking whether an optimizable space exists or not, and optimizing. And deploying the verified first power switching control model to a central control unit of the first new energy automobile to implement power switching management and control.

Through the transfer learning process, a large amount of driving data and control knowledge of the existing various types of power vehicle types can be fully utilized, a high-precision and stable power switching control model of the first new energy vehicle can be quickly obtained, and development cost and tuning time are greatly reduced.

In some possible embodiments of the present invention, in the step of controlling the sensor group to acquire first environmental data and first vehicle state data of an environment in which the first new energy automobile is located, the central control unit is configured to:

grouping the sensor groups to obtain a plurality of sensor subgroups;

acquiring first current position data of the first new energy automobile;

It can be appreciated that, in order to accurately collect data and reduce power consumption, in this embodiment, the sensor group includes, but is not limited to, a sensor disposed on the first new energy automobile and an internet of things sensor (such as a sensor disposed on another vehicle or an internet of things important facility and controlled and managed by an internet of things server) disposed outside the body of the first new energy automobile.

The sensor groups are grouped according to a preset first rule (such as a preset working state, a preset position, a preset working time length, attribute/functional characteristics of each sensor and the like) to obtain a plurality of sensor groups, (such as that a vehicle reaches the preset working state, a preset place, a preset working time length and the like).

Determining one or more corresponding first sensor subgroups from the plurality of sensor subgroups according to the first current position data (for example, when a first new energy automobile arrives at different preset positions, because each position corresponds to different environments, the detection functions of the corresponding sensor subgroups in a sensor group can be triggered in batches, for example, the sensor subgroups triggered by mud roads arriving at a certain mountain area are different from those triggered by asphalt ways arriving at an urban area), and triggering the first sensor subgroups to acquire the first environment data and the first vehicle state data.

In some possible embodiments of the present invention, the step of generating a first power switching control scheme for switching power of the first new energy automobile according to the first environmental data, the first vehicle state data and the first power switching control model, where the internet of things server is specifically configured to:

extracting motor state data, battery power data, engine state data, fuel oil data, air supply device data, and fuel cell data from the first vehicle state data;

It can be appreciated that in order to perform power switching control in a manner most appropriate to the current environment and current state of the first new energy automobile, in the embodiment of the present invention, road data (including but not limited to road gradient, road flatness, road pavement material, traffic conditions), temperature data, wind data, air pressure data, and air composition data are extracted from the first environment data; extracting motor state data, battery power data, engine state data, fuel oil data, air supply device data, and fuel cell data from the first vehicle state data; the first power switching control scheme is generated based on the road data, the temperature data, the wind power data, the air pressure data, the air composition data, the motor data, the battery power data, the engine state data, the fuel oil data, the air supply device data, the fuel cell data, and the like.

In some possible embodiments of the present invention, the internet of things server is configured to:

It can be appreciated that, in order to make the control of the vehicle more accurate and more fit to the needs of the user, in this embodiment, the voice data and the image data of the driver may be collected, and the voice data and the image data may be determined and analyzed to determine whether the first new energy automobile needs to perform the power system switching. When the first new energy automobile does not need to be subjected to power system switching, further, acquiring first navigation data and second current position data of the first new energy automobile; predicting first road segment environment data (including but not limited to data on road conditions, environment temperature, altitude, air composition, air pressure, wind speed, wind direction and the like) of a first road segment to be passed by the first new energy automobile in a preset first time according to the first navigation data and the second current position data; according to the first road section environment data, predicting a first power demand (or a first working mode demand) of the first new energy automobile when the first new energy automobile passes through the first road section by combining an environment-power demand model provided by a cloud server; determining whether a power system of the first new energy automobile can meet according to the first power demand and a first power matching model (comprising a system power matching range, a power efficiency maximizing strategy, an energy storage strategy and the like) of the first new energy automobile; when the power system of the first new energy automobile cannot meet the first power requirement, the vehicle state of the first new energy automobile is adjusted in advance, for example, an anti-skid device arranged on a hub is opened to increase the friction force of a tire; for another example, the ground contact area of the tire and the road surface and the uniformity of the ground contact area of each tire are optimized by adjusting the mounting position of the tire on the wheel, such as the gap between the rim and the hub on the outer side or the inner side of the tire, so that the operation stability and the emergency braking performance of the vehicle are improved; for another example, the vertical movement of the tire is influenced by changing parameters of the suspension system, such as spring stiffness, damping and the like, so that the contact performance of the tire and the road surface is optimized, and the operation stability, comfort and safety of the vehicle are comprehensively improved.

It will be appreciated that further, in combination with consideration of various aspects of performance matching, economy, and multi-mode compatibility, the first power matching model may further include the following to select the best engine, motor, and battery control scheme in combination balance:

drive wheel power demand: and calculating the power required by the driving wheel according to the parameters such as the weight of the whole vehicle, the peak power of the engine, the transmission ratio of the gearbox and the like, and taking the power as the basis for selecting the power of the motor, and usually selecting the motor with certain redundancy to meet the power requirement.

Pure electric endurance requirements: and selecting matched battery capacity and corresponding motor power according to the use habit of the user and the expected value of the pure electric endurance mileage, so that the electric energy consumption and the endurance mileage are balanced.

Fuel consumption limit: according to the lowest oil consumption characteristic of the engine under the rated working condition, the lowest oil consumption characteristic is matched with the selected motor power, the engine is limited to work in an ideal economic area, and the oil consumption is reduced to the maximum extent.

Matching power performance: and comprehensively considering power performance parameters of the engine and the motor, such as peak torque, torque characteristics and the like, and selecting the matched motor type and the engine so as to achieve acceleration and climbing performance expected by a user.

The multi-working mode is compatible, namely, the selected engine, motor and battery can support the switching of a plurality of working modes of the hybrid electric vehicle, such as an electric mode, a range-extending mode, a compound mode, a power compensation mode and the like, and can exert excellent performance in each mode.

Referring to fig. 2, another embodiment of the present invention provides a new energy automobile control method based on the internet of things, and the new energy automobile control system based on the internet of things is applied, where the new energy automobile control system based on the internet of things includes a cloud server, an internet of things server, a central control unit, a sensor group, a communication unit, a power switching unit, a fuel engine subsystem, a motor subsystem, an electronic storage system, and a fuel cell subsystem, and the new energy automobile control method based on the internet of things includes:

The cloud server acquires first production data and first test data of each minimum unit (such as a minimum assembly unit, a minimum part, a minimum component, a minimum structure and the like) of a first new energy automobile, and acquires whole vehicle test data and whole vehicle assembly data of the first new energy automobile;

the cloud server generates a first power switching control model of the first new energy automobile according to the first production data, the first test data, the whole vehicle assembly data and the initial power switching control model; the method comprises the steps of obtaining position information of a first new energy automobile by communicating with the first new energy automobile, and determining an Internet of things server to which the first new energy automobile is currently connected according to the position information of the first new energy automobile; the first power switching control model is sent to the Internet of things server currently connected with the first new energy automobile;

the central control unit controls the sensor group to acquire first environment data (including but not limited to environment control data, air composition data/pressure data, temperature data, humidity data, road surface data and the like) and first vehicle state data (including but not limited to fuel engine output power, rotating speed, oil consumption, cylinder pressure, engine oil pressure, maximum power, maximum torque, fault data, cooling liquid temperature, motor output power, battery power, charging times, air inlet temperature, exhaust temperature, vehicle speed, vehicle body quality, vehicle load, tire data, vehicle exterior shape/resistance data and the like) of the environment where the first new energy automobile is located;

the internet of things server generates a first power switching control scheme (including but not limited to a power range which can be output by each power supply mode, a requirement of the current environment/the current vehicle condition on power/vehicle speed, a requirement on power source safety, power switching time, a power transition mode and the like) for switching the power of the first new energy automobile according to the first environment data, the first vehicle state data and the first power switching control model.

And issuing a first power switching control scheme to the central control unit.

In some possible embodiments of the present invention, the step of generating, by the cloud server, a first power switching control model of the first new energy automobile according to the first working data, the first production data, the first test data, the whole vehicle assembly data, and the initial power switching control model includes:

In some possible embodiments of the present invention, the step of controlling the sensor group to acquire first environmental data and first vehicle state data of the environment in which the first new energy automobile is located by the central control unit includes:

grouping the sensor groups to obtain a plurality of sensor subgroups;

acquiring first current position data of the first new energy automobile;

In some possible embodiments of the present invention, the step of generating, by the internet of things server, a first power switching control scheme for switching power of the first new energy automobile according to the first environmental data, the first vehicle state data, and the first power switching control model includes:

In some possible embodiments of the present invention, the method further comprises:

It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, such as the above-described division of units, merely a division of logic functions, and there may be additional manners of dividing in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, or may be in electrical or other forms.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units described above, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the above-mentioned method of the various embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.

The foregoing has outlined rather broadly the more detailed description of embodiments of the application, wherein the principles and embodiments of the application are explained in detail using specific examples, the above examples being provided solely to facilitate the understanding of the method and core concepts of the application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.

Although the present application is disclosed above, the present application is not limited thereto. Variations and modifications, including combinations of the different functions and implementation steps, as well as embodiments of the software and hardware, may be readily apparent to those skilled in the art without departing from the spirit and scope of the application.

Claims

1. New energy automobile control system based on internet of things, characterized by comprising: the system comprises a cloud server, an Internet of things server, a central control unit, a sensor group, a communication unit, a power switching unit, a fuel engine subsystem, a motor subsystem, an electron storage subsystem and a fuel cell subsystem;

the cloud server is configured to:

The central control unit is configured to:

2. The new energy automobile control system based on the internet of things technology according to claim 1, wherein in the step of generating the first power switching control model of the first new energy automobile according to the first work data, the first production data, the first test data, the whole vehicle assembly data, and the initial power switching control model, the cloud server is specifically configured to:

3. The new energy vehicle control system based on the internet of things according to claim 2, wherein in the step of controlling the sensor group to acquire first environment data and first vehicle state data of an environment in which the first new energy vehicle is located, the central control unit is configured to:

grouping the sensor groups to obtain a plurality of sensor subgroups;

acquiring first current position data of the first new energy automobile;

4. The new energy automobile control system based on the internet of things technology according to claim 3, wherein the step of generating a first power switching control scheme for power switching of the first new energy automobile according to the first environmental data, the first vehicle state data, and the first power switching control model, the internet of things server is specifically configured to:

5. The new energy automobile control system based on the internet of things technology according to claim 4, wherein the internet of things server is configured to:

6. The new energy automobile control method based on the internet of things is characterized by applying a new energy automobile control system based on the internet of things, wherein the new energy automobile control system based on the internet of things comprises a cloud server, an internet of things server, a central control unit, a sensor group, a communication unit, a power switching unit, a fuel engine subsystem, a motor subsystem, an electron storage subsystem and a fuel cell subsystem, and the new energy automobile control method based on the internet of things comprises the following steps:

7. The method for controlling a new energy vehicle based on the internet of things according to claim 6, wherein the step of generating the first power switching control model of the first new energy vehicle by the cloud server according to the first working data, the first production data, the first test data, the whole vehicle assembly data, and the initial power switching control model includes:

8. The method for controlling a new energy vehicle based on the internet of things according to claim 7, wherein the step of controlling the sensor group to acquire first environmental data and first vehicle state data of an environment in which the first new energy vehicle is located by the central control unit includes:

grouping the sensor groups to obtain a plurality of sensor subgroups;

acquiring first current position data of the first new energy automobile;

9. The method for controlling a new energy vehicle based on the internet of things according to claim 8, wherein the step of generating, by the internet of things server, a first power switching control scheme for power switching of the first new energy vehicle according to the first environmental data, the first vehicle state data, and the first power switching control model includes:

10. The new energy automobile control method based on the internet of things technology of claim 9, further comprising: