Replacing conventional buses with electric buses is in line with the concept of sustainable development. However, electric buses have the disadvantages of short driving range and high purchase price. Many cities must implement a semi-electrification strategy for bus routes. In this paper, a bi-level, multi-objective programming model is established for the collaborative scheduling problem of vehicles and drivers on a bus route served by the mixed bus fleet. The upper-layer model minimizes the operation cost and economic cost of carbon emission to optimize the vehicle and charging scheme; while the lower-layer model tries to optimize the crew-scheduling scheme with the objective of minimizing driver wages and maximizing the degree of bus-driver specificity, considering the impact of drivers’ labor restrictions. Then, the improved multi-objective particle swarm algorithm based on an $\epsilon$-constraint processing mechanism is used to solve the problem. Finally, an actual bus route is taken as an example to verify the effectiveness of the model. The results show that the established model can reduce the impact of unbalanced vehicle scheduling in mixed fleets on crew scheduling, ensure the degree of driver–bus specificity to standardize operation, and save the operation cost and driver wage.

In the practical application of indoor air quality assurance system, it is difficult to detect the fault of air valves, CO2 sensors and other components, resulting in substandard air quality and increased energy consumption. In this paper, 16 fault conditions and 1 no fault condition were simulated by Simulink simulation software for primary return air conditioning system in summer, and a typical indoor air quality assurance system simulation fault characteristic table was obtained. It is found that PM2.5 sensor fault mainly affects indoor PM2.5 purification speed. The fault of a CO2 sensor affects indoor CO2 dilution and system energy consumption. Small resistance of return air valve increases system energy consumption. Small resistance of supply air valve, exhaust air valve and return air valve decreases the system's ability to control indoor pollutants.