Abstract
In order to increase the driving range of battery electric vehicles, while maintaining a high level of thermal comfort inside the passenger cabin, it is necessary to design an energy management system which optimally synthesizes multiple control actions of heating, ventilation and air-conditioning (HVAC) system. To gain an insight into optimal control actions and set a control benchmark, the paper first proposes an algorithm of dynamic programming (DP)-based optimisation of HVAC control variables, which minimises the conflicting criteria of passenger thermal comfort and HVAC efficiency. Next, a hierarchical structure of thermal comfort control system is proposed, which consists of optimised low-level feedback controllers, optimisation-based control allocation algorithm that sets references for the low-level controllers, and a superimposed cabin temperature controller that commands the cooling capacity to the allocation algorithm. Finally, the overall control system is verified by simulation for cool-down scenario, and the simulation results are compared with the DP benchmark. The results show that the control system behaviour can approach the DP benchmark if the superimposed controller bandwidth is tuned along with the allocation cost function weighting coefficients, where a fast controller tuning relates to better thermal comfort while a slow tuning results in improved efficiency.
Highlights
In recent years, electric vehicles have been increasingly adopted by public due to their superior energy efficiency and low or absent emissions
It is of great interest to achieve highest possible HVAC system efficiency, which would result in increased driving range, while maintaining high passenger thermal comfort
This is reflected in a relatively slow fall of cabin air temperature (Fig. 7a), relatively high evaporator outlet air temperature Tea,out (Fig. 7a), and correspondingly high evaporator air mass flow ṁ ea (Fig. 7c). Such control is beneficial for HVAC efficiency (Fig. 7f) as it enables the compressor to operate at low speeds (Fig. 7d), minimising its power consumption and maximising the coefficient of performance (COP)
Summary
Electric vehicles have been increasingly adopted by public due to their superior energy efficiency and low or absent emissions. It is of great interest to achieve highest possible HVAC system efficiency, which would result in increased driving range, while maintaining high passenger thermal comfort To fulfil these conflicting criteria, it is necessary to develop advanced control systems which optimally coordinate multiple actuators and energy storage units. This paper proposes a DP-based control trajectory optimisation method for an electric vehicle HVAC system, as well as a hierarchical/cascade control strategy that can approach the DP results. The presented case study is based on an A/C system model, the developed optimisation approach and the hierarchical control strategy can be applied to more complex HVAC systems, such as those utilised in advanced battery electric vehicles (Drage et al 2019).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
