Hybrid Electric Vehicle Energy Management With Battery Thermal Considerations Using Multi-Rate Dynamic Programming

2013 ◽  
Author(s):  
Rajit Johri ◽  
Wei Liang ◽  
Ryan McGee
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Computational Time ◽  
Bulk Temperature ◽  
Thermal Dynamics ◽  
Battery Thermal Management ◽  
Battery Capacity ◽  
Hybrid Electric

Battery capacity and battery thermal management control have a significant impact on the Hybrid Electric Vehicle (HEV) fuel economy. Additionally, battery temperature has a key influence on the battery health in an HEV. In the past, battery temperature and cooling capacity has not been included while performing optimization studies for power management or optimal battery sizing. This paper presents an application of Dynamic Programming (DP) to HEV optimization with battery thermal constraints. The optimization problem is formulated with 3 state variables, namely, the battery State Of Charge (SOC), the engine speed and the battery bulk temperature. This optimization is critical for determining appropriate battery size and battery thermal management design. The proposed problem has a major challenge in computation time due to the large state space. The paper describes a novel multi-rate DP algorithm to reduce the computational challenges associated with the particular class of large-scale problem where states evolve at very different rates. In HEV applications, the battery thermal dynamics is orders of magnitude slower than powertrain dynamics. The proposed DP algorithm provides a novel way of tackling this problem with multiple time rates for DP with each time rate associated with the fast and slow states separately. Additionally, the paper gives possible numerical techniques to reduce the DP computational time and the time reduction for each technique is shown.

Experimental and Theoretical Efficiency Investigation of Hybrid Electric Vehicle Battery Thermal Management Systems

2014 ◽  
Vol 136 (1) ◽  
Author(s):  
H. S. Hamut ◽  
I. Dincer ◽  
G. F. Naterer
Keyword(s):  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Operating Conditions ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
Electric Vehicle Battery ◽  
Hybrid Electric ◽  
Reported Data

In this study, a thermodynamic model of a hybrid electric vehicle battery thermal management system (TMS) is developed and the efficiency of the system is determined based on different parameters and operating conditions. Subsequently, a TMS test bench is used with a production vehicle (Chevrolet Volt) that is fully instrumented in order to develop a vehicle level demonstration of the study. The experimental data are acquired under various conditions using an IPETRONIK data acquisition system, along with other reported data in the literature, to validate the numerical model results. Based on the analyses, the condenser and evaporator pressure drop, compressor work and compression ratio, evaporator heat load and efficiency of the system are determined both numerically and experimentally. The predicted results are determined to be within 6% of the conducted experimental results and within 15% of the reported results in the literature.

Optimal Energy Management in a Range Extender PHEV Using a Cascaded Dynamic Programming Approach

2018 ◽  
Author(s):  
Pradeep Sharma Oruganti ◽  
Daniel Jung ◽  
Mukilan Arasu ◽  
Qadeer Ahmed ◽  
Giorgio Rizzoni
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Computation Time ◽  
The Other ◽  
Computational Time ◽  
Programming Approach ◽  
Full Model ◽  
Hybrid Electric ◽  
And Control

Dynamic programming is widely used to benchmark the performance of a hybrid electric vehicle. It is also well documented that it is a very computationally heavy procedure depending on the number of states and control inputs in the problem formulation. In this paper we investigate the possibility of reduction in the computational time by splitting the number of states and control inputs between two models and applying dynamic programming individually, using the output of one as an input to the other and hence cascading the two models. A range extended hybrid electric vehicle powertrain architecture is modeled with four states and four control inputs, which is considered as the full model. Further, the states and control inputs of the battery and engine are separated from the other states, splitting them between the two new DP models. The vehicle performance estimated from this ‘cascaded models approach’ is compared with that from the full model. Initial comparisons show a very good match with minor differences in performance and considerable a reduction in computation time from around 6 hours to around a minute.

Modeling of Thermal Dynamics of a Connected Hybrid Electric Vehicle for Integrated HVAC and Powertrain Optimal Operation

2019 ◽  
Author(s):  
Nehal Doshi ◽  
Drew Hanover ◽  
Sadra Hemmati ◽  
Christopher Morgan ◽  
Mahdi Shahbakhti
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Optimal Operation ◽  
Operating Conditions ◽  
System Level ◽  
Electric Heater ◽  
Ambient Conditions ◽  
Ic Engine ◽  
Thermal Dynamics ◽  
Hybrid Electric

Abstract Integrated energy management across system level components in electric vehicles (EVs) is currently an under-explored space. Opportunity exists to mitigate energy consumption and extend usable range of EVs through optimal control strategies which exploit system dynamics via controls integration of vehicle subsystems. Additionally, information available in connected vehicles like driver schedules, trip duration and ambient conditions can be leveraged to predict the operating conditions for a vehicle when a validated model of the vehicle is known. In this study, data-driven and physics-based models for heating, ventilation and air-conditioning (HVAC) are developed and utilized along with the vehicle dynamics and powertrain (VD&PT) models for a hybrid electric vehicle (HEV). The integrated HVAC and VD&PT models are then validated against real world data. Next, an integrated relationship between the internal combustion (IC) engine coolant and the cabin electric heater is established and used to promote potential energy savings in cabin heating when the operating schedule is known. Finally, an optimization study is conducted to establish a control strategy which maximizes the HVAC energy efficiency whilst maintaining occupant comfort levels according to ASHRAE standards and improving usable range of the vehicle relative to its baseline calibration.

Sign in / Sign up

Export Citation Format

Share Document