On the Optimal Thermal Management of Hybrid-Electric Vehicles with Heat Recovery Systems

Merz, Fabien; Sciarretta, Antonio; Dabadie, Jean-Charles; Serrao, Lorenzo · 2012 · OpenAlex-citations

DOI: 10.2516/ogst/2012017

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses the challenge of optimizing energy management in Hybrid Electric Vehicles (HEVs) by integrating thermal dynamics into the control strategy. Traditional HEV optimization focuses primarily on battery State of Charge (SOC) to minimize fuel consumption or emissions, often neglecting the significant impact of temperature-dependent phenomena. The authors argue that thermal processes, such as engine warm-up, catalytic converter light-off, and heat recovery, have characteristic timescales comparable to or longer than mechanical dynamics, making them critical for overall efficiency. The study aims to develop a generalized framework that combines optimal powertrain supervisory control with thermal management, specifically incorporating exhaust aftertreatment and exhaust heat recovery systems. The methodology employs a control-oriented Reduced-Order Model (ROM) derived from a detailed Full-Order Model (FOM) of a power-split HEV equipped with a gasoline engine, electric motors, and a lithium-ion battery. The ROM simplifies complex thermal behaviors into lumped temperature states, including engine coolant/oil temperature, exhaust/catalyst temperature, and Rankine-cycle dynamics. The authors apply Pontryagin’s Minimum Principle (PMP) to derive optimal control strategies. A key innovation is the introduction of a "fuel equivalent" for thermal energy variations, analogous to the equivalence factors used in the Equivalent Consumption Minimization Strategy (ECMS) for battery energy. This allows thermal states to be treated as cost variables within the optimization framework. The study evaluates four optimization scenarios (S0–S3) with increasing complexity regarding included thermal dynamics and compares these PMP-based strategies against a heuristic, rule-based strategy. The results demonstrate that incorporating thermal dynamics into the optimization process yields significant benefits in both fuel economy and pollutant emission reduction. By explicitly managing thermal states, the optimal strategies can better coordinate engine operation to accelerate catalyst light-off and maximize heat recovery efficiency, particularly during cold-start scenarios. The PMP-derived strategies outperform the heuristic rule-based approach, validating the effectiveness of the proposed framework. The introduction of thermal equivalence factors proves effective in balancing the trade-offs between immediate fuel consumption and long-term thermal benefits, such as maintaining catalyst temperature or harvesting exhaust heat. The significance of this work lies in its contribution to the field of vehicle electrification by providing a rigorous mathematical framework for holistic energy management. It demonstrates that thermal management is not merely a passive subsystem but an active component that can be optimized alongside electrical energy flows. The findings suggest that future HEV control strategies should integrate thermal dynamics to achieve maximum efficiency and emission compliance, particularly for vehicles equipped with advanced aftertreatment and heat recovery systems. This approach offers a promising direction for improving the environmental performance of hybrid vehicles without requiring additional hardware complexity.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• eco driving