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.