Path planning method for pure electric garbage truck based on electricity forecast and intelligent energy management
A technology of energy management and path planning, which is applied in measuring devices, surveying and navigation, road network navigators, etc., and can solve problems such as large estimation errors and increased vehicle mass
Active Publication Date: 2020-11-17
WUHAN UNIV OF TECH
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Problems solved by technology
However, for pure electric garbage trucks, the mass of the vehicle will increase significantly after loading operations, and estimating the vehicle's power condition based on the driving records of the previous period will result in a large estimation error
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[0029] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0030] Such as Figures 1 to 2 As shown, a pure electric garbage truck power prediction and intelligent energy management method,
[0031] The pure electric garbage truck includes: GPS, BMS and load cell; wherein, GPS is used for map navigation of garbage sites, dumping points and charging site locations near the garbage truck;
[0032] BMS (Battery Management System) calculates the current SOC of the battery through the current battery terminal voltage U, current I and temperature T;
[0033] The load cell obtains each garbage quality of each garbage collection site;
[0034] Including the following steps:
[0035] Ste...
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The invention discloses a method for planning a path of an all-electric garbage truck based on electric quantity prediction and intelligent energy management. The method comprises the following steps:obtaining garbage mass of each garage collection station through aweighing sensor on the all-electric garbage truck when collecting garbage each time, and predicting garbage amount of each station in the future based on big data statistics and self-learning of the truck; lifting all truck driving schemes according to the stations needing collection by the truck, and respectively calculating truck energy consumption and truck remaining electricity quantities of two adjacent stations on account of the schemes; calculating final remaining battery energy of the truck for corresponding driving paths according to the schemes, and comparing final remaining battery electricity quantities of the schemes, and taking a path of a scheme with a maximum remaining battery electricity quantity as an optimal driving route for the truck. The method is capable of considering the influence of loading mass of the garbage truck on the energy consumption, improving the prediction accuracy of the electricity quantity of the all-electric garbage truck, reducing the energy consumption of the garbage truck and increasing the garbage transportation amount.
Description
technical field [0001] The invention relates to vehicle intelligent control technology, in particular to a path planning method for pure electric garbage trucks based on electric quantity prediction and intelligent energy management. Background technique [0002] Driven by the joint promotion of energy-saving and emission-reduction demands and government subsidies, restrictions on travel and purchase, and double points, China's sanitation vehicle market is currently ushering in the "golden age" of new energy vehicle development. Compared with traditional fuel garbage trucks, the mileage of electric garbage trucks is limited by the energy density of on-board batteries and manufacturing costs, and the infrastructure such as charging stations or charging plants is still far from perfect. How to predict the power of electric garbage trucks And intelligent energy management becomes particularly important. [0003] The focus of enterprises on electric vehicle power forecasting an...
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IPC IPC(8): G01C21/34
CPCG01C21/3469G01C21/3476
Inventor 杜常清黄志波武冬梅颜伏伍
Owner WUHAN UNIV OF TECH