Take the energy saving and reduction of energy consumption of public transportation companies as an example.

To reduce the energy consumption of public transportation, the first thing you need to know is why some vehicles/drivers have high energy consumption? Some are low? What are the factors that have an impact on energy consumption? In response to these questions, we can find that the main factors affecting the energy consumption of public transportation include: vehicle conditions, driving behavior, traffic conditions, the environment, the main power-consuming components work and so on.

Further analysis, in the driving behavior of this factor, the impact on energy consumption depends on gas pedal depth, brake pedal depth, average speed, the length of time to step on the gas pedal, the length of time to step on the brake, and the smoothness of acceleration and other aspects. Among the usage of power-consuming components, air conditioner on time, air conditioner set temperature also have a big impact on energy consumption.

With so many relevant factors, and the intricate relationship between the influences, what can be done to minimize energy consumption? We can use big data to analyze the energy saving and consumption reduction model of the bus company, multi-dimensional comparative analysis of the reasons for the difference in energy consumption, to understand the level of energy consumption of the bus company, to find out the high energy consumption of drivers and vehicles, so as to make precise adjustments to reduce energy consumption.