Battery thermal management is critical for electric vehicles operating in cold climates, where low temperatures reduce battery efficiency, limit regenerative braking and accelerate degradation. This study compares PTC heater and heat pump systems for battery thermal management in electric minibuses using optimization-based control strategies. A control-oriented model of the vehicle thermal system, validated against chassis dynamometer measurements, and a heat pump system model, validated against testbed measurements, are used to optimize thermal management strategies via nonlinear programming, minimizing energy consumption while accounting for Joule losses, regenerative braking energy and thermal system consumption. Battery degradation is evaluated using a Doyle-Fuller-Newman (DFN) electrochemical model incorporating physics-based degradation mechanisms. Results show that optimized thermal management strategies can simultaneously reduce energy consumption and degradation. With the PTC heater system, only marginal improvements are achievable, and further reductions in degradation come at the cost of increased energy consumption. In contrast, the more efficient heat pump system enables simultaneous reductions in both degradation and energy consumption through optimized thermal management. These findings highlight that advanced thermal management leveraging heat pump systems can enhance both driving range and battery lifetime in cold-climate electric vehicle operations.

The shift towards sustainable mobility in the passenger- and transport sectors is driving the development of sustainable propulsion technologies. Alongside the advancement of efficient and sustainable powertrains, research increasingly targets the optimization of development processes to address rising system complexity and reduce engineering effort. With the growing adoption of Battery Electric Vehicles (BEVs) and Fuel Cell Electric Vehicles (FCEVs), thermal management is becoming a critical part of the overall vehicle energy management. Considering electric commercial vehicles for public transport, one of the main challenges – beyond the optimal thermal conditioning of powertrain components – is the efficient thermal management of the passengers’ cabin, which significantly impacts overall energy consumption, vehicle range and thermal comfort especially at cold ambient conditions. Particular attention must be paid to the interaction between the Heating, Ventilation and Air Conditioning (HVAC) system and the thermal management system (TMS) of the powertrain components, as can be found in state-of-the-art heat pump systems for electrified vehicles. To enable the early development of operating strategies while accounting for system interactions and determining the optimal system layout, an integrated approach is applied that combines simulation with testing on the Hardware-in-the-Loop (HiL)-ThermoLab testbed. This approach is used in the EU Horizon Europe research project MINDED improving the energy consumption of a battery-electric IVECO eDaily minibus at 0 °C ambient temperature. For the development of optimal HVAC layouts and efficient operating strategies, a multi-physical 1D digital twin model of the passenger cabin, described with the modeling language Modelica and validated with measurement results, is used, while all key refrigerant- and thermal circuit components are physically implemented on the testbed. Hardware components that are not yet available are substituted and necessary environment boundary conditions are emulated on the HiL-ThermoLab testbed using novel dynamic thermo-hydraulic emulators. With the presented methodology and the experimental tests conducted under its application, a simplified heat pump system is developed and investigated for the identification of potentials to reduce energy consumption in the battery-electric IVECO eDaily minibus. The results demonstrate that the HiL-ThermoLab provides an optimal testing environment for identifying efficiency potentials, while the combined use of simulation and hardware testing significantly reduces engineering effort and enables the development of advanced energy management systems at an early development stage.