Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies
Source abstract
Abstract
This paper presents a comprehensive review of energy management control strategies utilized in hybrid electric vehicles (HEVs). These can be categorized as rule-based strategies and optimization-based strategies. Rule-based strategies, as the most basic strategy, are widely used due to their simplicity and practical application. The focus of rule-based strategies is to determine and optimize the optimal threshold for mode switching; however, they fall into a local optimal solutions. To have better performance in energy management, optimization-based strategies were developed. The categories of the existing optimization-based strategies are identified from the latest literature, and a brief study of each strategy is discussed, which consists of the main research ideas, the research focus, advantages, disadvantages and improvements to ameliorate optimality and real-time performance. Deterministic dynamic programming strategy is regarded as a benchmark. Based on neural network and the large data processing technology, data-driven strategies are put forward due to their approximate optimality and high computational efficiency. Finally, the comprehensive performance of each control strategy is analyzed with respect to five aspects. This paper not only provides a comprehensive analysis of energy management control strategies for HEVs, but also presents the emphasis in the future.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electric and Hybrid Vehicle Technologies · Advanced Battery Technologies Research · Electric Vehicles and Infrastructure
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
General R&D Institute of China FAW, Changchun 130011, China
Funding
National Natural Science Foundation of China · Jilin Province Science and Technology Development Fund · the Energy Administration of Jilin Province
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