Optimization of the Energy-Comfort Trade-Off of HVAC Systems in Electric City Buses Based on a Steady-State Model

TL;DR

This paper develops a steady-state thermal model to optimize the energy consumption and passenger comfort of HVAC systems in electric city buses, enabling efficient design and control strategies for improved performance.

Contribution

It introduces a simplified steady-state modeling approach for HVAC optimization in electric buses, validated against dynamic simulations, facilitating practical design and control improvements.

Findings

Steady-state model closely matches dynamic simulation results.

Method enables year-round HVAC performance evaluation.

Setpoints derived for online controllers improve energy efficiency.

Abstract

The electrification of public transport vehicles offers the potential to relieve city centers of pollutant and noise emissions. Furthermore, electric buses have lower life-cycle greenhouse gas (GHG) emissions than diesel buses, particularly when operated with sustainably produced electricity. However, the heating, ventilation, and air-conditioning (HVAC) system can consume a significant amount of energy, thus limiting the achievable driving range. In this paper, we address the HVAC system in an electric city bus by analyzing the trade-off between the energy consumption and the thermal comfort of the passengers. We do this by developing a dynamic thermal model for the bus, which we simplify by considering it to be in steady state. We introduce a method that is able to quickly optimize the steady-state HVAC system inputs for a large number of samples representative of a year-round operation. A comparison between the results from the steady-state optimization approach and a dynamic simulation reveals small deviations in both the HVAC system power demand and achieved thermal comfort. Thus, the approximation of the system performance with a steady-state model is justified. We present two case studies to demonstrate the practical relevance of the approach. First, we show how the method can be used to compare different HVAC system designs based on a year-round performance evaluation. Second, we show how the method can be used to extract setpoints for online controllers that achieve close-to-optimal performance without any predictive information. In conclusion, this study shows that a steady-state analysis of the HVAC systems of an electric city bus is a valuable approach to evaluate and optimize its performance.