Reinforcement Learning Based Intelligent Fan Controller

In Automotive world, vehicle development includes design and testing of hardware and software. Hardware includes components required for actuation and sensing, along with the controller hardware. Software includes control logic embedded in controller for functioning of these components. Generally, software inside controller could be validated in various ways e.g., Software in Loop (SiL), Hardware in Loop (HiL), Vehicle testing. During initial phase of control software development cycle, plant models with adequate accuracy replicating hardware components are utilized for digital software validation. Many a times, hardware components might be available before control software matures. Hence, to validate plant models for their accuracy & quality alternate option of actual controller is needed during initial phase. Intelligent controller mimicking original controller can be an alternate option for plant model improvement and component level performance analysis. This paper proposes a Reinforcement Learning (RL) based intelligent controller for controlling Fan actuator of thermal management system of an electrical vehicle. In simulation world, this becomes advantageous from resource availability point of view, especially during initial phase of control software development. The same methodology can be extended to other components of system as well.