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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.07559 |
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| _version_ | 1866913196854476800 |
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| author | Ma, Zhipeng Jørgensen, Bo Nørregaard Ma, Zheng Grace |
| author_facet | Ma, Zhipeng Jørgensen, Bo Nørregaard Ma, Zheng Grace |
| contents | The transportation industry remains a significant contributor to greenhouse gas emissions, highlighting the requirement for intelligent systems to enhance vehicle energy efficiency. The intellectual property rights of developed systems should be protected by patents. However, there is no patent overview of eco-driving intelligent systems. Unlike a scientific article, a patent documentation indicates both novelty and commercialization potential of an inventor. To address this research gap, this paper provides a patent overview of eco-driving intelligent systems and algorithms. 424 patents in the Google Patent database are analyzed. The patent analysis results show that the top three Cooperative Patent Classifications are: Y02T - climate change mitigation technologies related to transportation (50.7%), B60W - Conjoint control of vehicle subunits of different types or different functions (34.4%) and B60L - Propulsion of electrically-propelled vehicles (20.2%). 219 patents were filed after 2016 when deep learning became popular and can be categorized into five groups: vehicle energy management, smart driving, ecological and sustainable driving, fuel consumption reduction, and driving behavior optimization. Furthermore, all 219 patents involve the physical components of the intelligent system and/or novel machine learning/deep learning algorithms. Moreover, over 70% of them are granted by the China National Intellectual Property Administration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_07559 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Eco-driving Intelligent Systems and Algorithms: A Patent Review Ma, Zhipeng Jørgensen, Bo Nørregaard Ma, Zheng Grace Systems and Control The transportation industry remains a significant contributor to greenhouse gas emissions, highlighting the requirement for intelligent systems to enhance vehicle energy efficiency. The intellectual property rights of developed systems should be protected by patents. However, there is no patent overview of eco-driving intelligent systems. Unlike a scientific article, a patent documentation indicates both novelty and commercialization potential of an inventor. To address this research gap, this paper provides a patent overview of eco-driving intelligent systems and algorithms. 424 patents in the Google Patent database are analyzed. The patent analysis results show that the top three Cooperative Patent Classifications are: Y02T - climate change mitigation technologies related to transportation (50.7%), B60W - Conjoint control of vehicle subunits of different types or different functions (34.4%) and B60L - Propulsion of electrically-propelled vehicles (20.2%). 219 patents were filed after 2016 when deep learning became popular and can be categorized into five groups: vehicle energy management, smart driving, ecological and sustainable driving, fuel consumption reduction, and driving behavior optimization. Furthermore, all 219 patents involve the physical components of the intelligent system and/or novel machine learning/deep learning algorithms. Moreover, over 70% of them are granted by the China National Intellectual Property Administration. |
| title | Eco-driving Intelligent Systems and Algorithms: A Patent Review |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2401.07559 |