Optimal Control of an Integrated Energy and Thermal Management System for Electrified Powertrains

Wei, Caiyang; Hofman, Théo; Caarls, Esin Ilhan; Iperen, Rokus van

doi:10.23919/acc.2019.8815244

Cited by 9 publications

(5 citation statements)

References 14 publications

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“…It achieves a close-to-optimal solution by taking advantages of DP, PMP, and ECMS algorithms. These results extend the work presented in [34]. The rest of this paper is organized as follows.…”

Section: Introductionsupporting

confidence: 85%

Integrated Energy and Thermal Management for Electrified Powertrains

Wei

Hofman

Caarls³

et al. 2019

Energies

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This study presents an integrated energy and thermal management system to identify the fuel-saving potential caused by cold-starting an electrified powertrain. In addition, it quantifies the benefit of adopting waste heat recovery (WHR) technologies on the ultimate fuel savings. A cold-start implies a low engine temperature, which increases the frictional power dissipation in the engine, leading to excess fuel usage. A dual-source WHR (DSWHR) system is employed to recuperate waste heat from exhaust gases. The energy harvested is stored in a battery and can be retrieved when needed. Moreover, the system recovers waste heat from an electric machine, including power electronics and a continuous variable transmission, to boost the heating performance of a heat pump for cabin heating. This results in a decrease in the load on the battery. The integrated energy and thermal management system aims at maximizing the fuel efficiency for a pre-defined drive cycle. Simulation results show that cold-start conditions affect the fuel-saving potential significantly, up to 7.1% on the New European Driving Cycle (NEDC), yet have a small impact on the optimal controller. The DSWHR system improves the fuel economy remarkably, up to 13.1% on the NEDC, from which the design of WHR technologies and dimensioning of powertrain components can be derived. As the optimal solution is obtained offline, a complete energy consumption minimization strategy framework, considering both energy and thermal aspects, is proposed to enable online implementation.

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Section: Introductionsupporting

confidence: 85%

Integrated Energy and Thermal Management for Electrified Powertrains

Wei

Hofman

Caarls³

et al. 2019

Energies

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“…The engine's fuel consumption needs to be corrected [4,8]. When this temperature reaches above 80 °C, the effect of temperature on fuel consumption is negligible [9]. Van Berkel et al [10] considered the effect of engine lubricant temperature on fuel consumption when applying a dynamic planning energy management strategy.…”

Section: Introductionmentioning

confidence: 99%

Research on Energy Management Strategy of Range Extender Electric Vehicle considering Temperature Effect under Different Heat Demands

Li³

2023

International Journal of Energy Research

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In order to further improve the energy utilization of the range extender electric vehicle (REEV), the energy management strategy of the REEV under different heat demands and operating temperatures is studied. Firstly, for reducing the extra fuel consumption caused by engine operating temperature, the influence of engine lubricating oil temperature on the equivalence factor is analyzed, and a novel method is proposed, which can determine the equivalence factor by three parameters, including engine temperature, operating condition type, and battery state of charge (SOC). Secondly, to reduce the influence of frequent engine start/stop on fuel consumption, a method to establish the penalty factor based on battery SOC is proposed. Finally, the engine temperature rise law under low-temperature environment and the compressor drive mode determination method under high-temperature environment are studied according to the heat demand under different ambient temperatures. An adaptive equivalent consumption minimization strategy (ECMS) considering the effect of temperature under different heat demands is proposed on the basis of the above research. The simulation under the worldwide harmonized light vehicle test cycle (WLTC) drive cycle reveals that by using the adaptive ECMS, the vehicle operating cost is reduced by 5.69% in normal temperature environment, 0.53%-2.39% in a low-temperature environment, and 0.2%-2.01% in a high-temperature environment.

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“…Furthermore, the cold engine and ambient temperatures affect the aftertreatment system leading to an interaction between fuel economy and emission reduction at low ambient temperatures [19]. Despite the considerable impact of engine, battery, and aftertreatment thermal management on the HEV fuel economy and efficiency, only a few references [20][21][22][23][24] have addressed integrated power and thermal management (iPTM) of HEVs.…”

Section: Introductionmentioning

confidence: 99%

“…The conventional EMS designed for HEVs at normal operating conditions can be extended to handle iPTM with additional thermal states. In [22], influence of the coldstart on the fuel consumption was studied using DP. In [23], a thermal state was considered reflecting the engine temperature and PMP was applied to a two-state model.…”

Section: Introductionmentioning

confidence: 99%

Engine and Aftertreatment Co-Optimization of Connected HEVs via Multi-Range Vehicle Speed Planning and Prediction

Hu¹,

Amini²,

Feng³

et al. 2020

Preprint

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Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-tovehicle (V2V) communications-based information, is difficult and error-prone.The multiple timescales inherent to power and thermal systems call for a variable timescale optimization framework with access to short-and long-term vehicle speed preview. To this end, a model predictive controller (MPC) with a multi-range speed preview for integrated power and thermal management (iPTM) of connected hybrid electric vehicles (HEVs) is presented in this paper. The MPC is formulated to manage the power-split between the engine and the battery while enforcing the power and thermal (engine coolant and catalytic converter temperatures) constraints. The MPC exploits prediction and optimization over a shorter receding horizon and longer shrinking horizon. The vehicle speed is predicted (or planned in case of eco-driving) based on V2I communications over the shorter receding horizon. Over the longer shrinking horizon, the vehicle speed estimation is based on the data collected from the connected vehicles traveling on the same route as the ego-vehicle. Simulation results of applying the MPC over real-world urban driving cycles in Ann Arbor, MI are presented to demonstrate the effectiveness and fuel-saving potentials of the proposed iPTM strategy under the uncertainty associated with long-term predictions of the CV's speed.

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Optimal Control of an Integrated Energy and Thermal Management System for Electrified Powertrains

Cited by 9 publications

References 14 publications

Integrated Energy and Thermal Management for Electrified Powertrains

Integrated Energy and Thermal Management for Electrified Powertrains

Research on Energy Management Strategy of Range Extender Electric Vehicle considering Temperature Effect under Different Heat Demands

Engine and Aftertreatment Co-Optimization of Connected HEVs via Multi-Range Vehicle Speed Planning and Prediction

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