Smart Parking Recommendation for Vehicle Thermal Energy Saving
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Solution Overview
Problem
Existing vehicle passenger compartment thermal management systems consume significant energy and impact vehicle range and efficiency, as they often rely on HVAC systems without effectively utilizing the vehicle's surroundings.
Innovation Solution
A smart parking recommendation system using sensors, actuators, and AI/ML models to optimize solar and wind exposure for thermal management, reducing reliance on HVAC systems by suggesting and guiding vehicles to park in spots that minimize energy consumption while maintaining thermal comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If traditional HVAC systems are used to manage thermal quality of vehicle passenger compartments, then thermal comfort is maintained, but energy consumption increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-cooling or pre-heating the passenger compartment before the vehicle is parked, and by pre-positioning the vehicle in optimal parking spots with favorable thermal characteristics (shade, wind protection, proximity to thermal mass). This advance preparation reduces the thermal load during parking, minimizing the need for energy-consuming HVAC operation while maintaining thermal comfort.
Solution Approach 2:
The system introduces intermediary elements such as utilizing the vehicle's own thermal mass, employing phase change materials, using the surrounding environment (shade from buildings/trees, wind patterns, nearby water bodies) as thermal buffers, and leveraging the vehicle's battery thermal management system as an auxiliary heating or cooling source. These intermediaries reduce the direct burden on the primary HVAC system.
2Temperature
If HVAC systems operate continuously to maintain thermal comfort, then passenger compartment temperature is controlled, but vehicle range decreases
Solution Approach 1:
The system performs preliminary thermal conditioning of the passenger compartment before parking occurs, and pre-positions the vehicle in optimal parking locations with favorable thermal characteristics. This advance preparation creates a thermal buffer that extends the duration the vehicle can remain parked without HVAC operation, thereby preserving range for actual driving needs.
Solution Approach 2:
The system converts previously wasted thermal energy into useful resources. For example, it captures waste heat from the battery thermal management system or exhaust (in hybrid vehicles) and redirects it for cabin heating. It also utilizes the natural thermal inertia of the vehicle structure and surrounding environment as beneficial thermal buffers, turning passive thermal mass into an active range-extending resource.
3Use of energy by moving object
If AI/ML models and sensors are added to optimize parking recommendations, then energy consumption is reduced, but device complexity increases
Solution Approach 1:
The system achieves multi-functionality by utilizing existing vehicle components for multiple purposes: the battery thermal management system serves both battery temperature control and cabin heating/cooling assistance; the sensor suite originally designed for autonomous driving or safety features is repurposed to detect thermal characteristics of parking environments; the infotainment and communication systems are used for receiving and processing parking recommendation data. This approach reduces energy consumption through smart parking optimization without requiring dedicated new hardware for each function.
Solution Approach 2:
The system implements self-service by using the vehicle's own existing resources and data to make parking decisions. The vehicle's sensors autonomously detect environmental thermal characteristics, the onboard processor runs AI/ML models to evaluate parking spots, and the system automatically communicates with parking infrastructure or recommends spots to the driver without requiring external complex infrastructure. The vehicle essentially recommends its own optimal parking locations using its own capabilities.
Data Source
AI summary
A smart parking recommendation system for energy conservation in a vehicle includes a smart parking recommendation application (SPRA) that determines that enabling conditions have been met and obtains from sensors and actuators of the vehicle, information about the vehicle and the vehicle's environment. The SPRA monitors information from the sensors and actuators and obtained from remote computing resources, a vehicle operator's current vehicle usage and determines a typical parking duration for a current parking location, and categorizes the current parking location. The SPRA utilizes an artificial intelligence (AI) or machine learning (ML) model to suggest a parking spot within the parking location that satisfies user and energy consumption passenger compartment thermal quality preferences. The SPRA selectively parks or guides the vehicle to be parked within a parking spot that satisfies the constraints and preferences, and minimizes energy consumption for maintaining passenger compartment and battery thermal qualities.