{'fraction_non_alphanumeric': 0.015416238437821172, 'fraction_numerical': 0.0, 'mean_word_length': 5.324675324675325, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Predictive energy management for hybrid electric vehicles considering extension of the battery life

Hybrid electric vehicles offer potential for reducing the oil consumption and the generation of greenhouse gases, but they have a high battery price and short battery longevity. This paper presents an energy management strategy for power-split hybrid electric vehicles, which seeks not only to reduce the gasoline consumption but also to prolong the battery life. The instantaneous battery usage is penalized by its influence on the battery lifespan. This influence is defined by a new concept of battery ageing, i.e. the battery-fading index, which represents the ageing rate of the battery in various conditions. The multi-objective optimization problem is achieved by a model predictive control framework. The results indicate that the proposed energy management strategy effectively reduces battery fading with only a relatively small increase in the fuel consumption.