Projects:2019s1-131 Fuel Cell Hybrid Vehicle: Energy Management and AI-Enable Intelligent Control

Project team

Project members

• Loqman Al Hakim Aripin
• Jan Zhen Pang
• Tsz Yee Ha

Supervisors

• Prof. Cheng Chew Lim
• Prof. Peng Shi

Technical advisor

• Mr. Di Shen

Introduction

Why Fuel Cell Hybrid Vehicle?

Fuel cell hybrid vehicle uses hydrogen gas to fuel the vehicle. Compared to a conventional vehicle, this vehicle produces zero-emission since it only emits water vapour. This is one of the solutions for an eco-friendly vehicle. In addition, fuel cell hybrid vehicle does not need to charge the battery since it capable to maintain the battery SoC at a certain level. This has the advantages over the pure electric vehicle which need to take a long period of time to fully charge the battery.

In order to maintain the State of Charge (SoC) of the battery, the energy flow inside the FCHV needs to be regulated. This motivates the project to develop a Power Control Unit (PCU) to regulate the energy flow between fuel cell and the battery.

However, the SoC of a battery is practically not observable. This requires the team to develop a Battery Management Strategy to estimate the SoC of the battery.

Aim

The aims of this project are:

• Develop a PCU for the Energy Management Strategy where it capable to:
  • Minimise the total hydrogen fuel consumption
  • Maintain the SoC of the battery
• Develop a Battery Management System to estimate the SoC of the battery.
• Develop a fully functional simulator to analyse the performance of the PCU

Background

Fuel Cell Hybrid Vehicle

In recent years, the development of hybrid vehicles increases dramatically where hybrid electric vehicles (HEVs) are widely used throughout the world. The term hybrid vehicle generally means that the vehicle uses one or more different form of power sources to power up the vehicle. In this project, we will focus on Fuel Cell Hybrid Vehicle (FCHV), where it uses hydrogen gas as fuel to power the vehicle. In addition, the battery pack is also added to act as energy storage and provide sufficient energy to the vehicle when necessary.

Moreover, FCHV consists of several modes during operation such as fuel cell mode, hybrid mode, battery mode and regenerative braking mode which is shown in Figure 1 below. Based on Figure 1, the FCHV mainly uses the combination of the FCS, battery pack, motor driver and DC-DC converter. A PCU is needed in order to regulate and control multiple power sources of the FCHV.

Methodology

Power Plant

FCHV system mainly uses the combination of PEM fuel cell stack, DC-DC converter, PCU, 24V Nickel Metal Battery Pack, Electric Motor and Motor Driver. DC-DC converter plays an important role in the powerplant of the FCHV because DC-DC converter can control and regulate the energy flow of the FCHV. On top of that, the DC-DC converter receives the signal from the PCU to change the desired output requested by the PCU. Based on the Figure below, all the information of the powerplant is sent to the PCU and PCU will send a control signal action to the DC-DC converter. Therefore, an energy management system is required to regulate the energy flow.

The specification of each of the components in the powerplant of the FCHV is listed as shown below.

• Fuel Cell Stack
  • Type of Fuel Cells: PEM
  • Number of Cells: 14 cells
  • Rated Power: 30W
  • Performance: 8.4V/3.6A
• DC-DC Converter
  • Input Range: 8-14V
  • Output Range: 15-25V, 1.2-2A
• Battery Pack
  • Type: Nickel Metal
  • Specification: 24V 3000mAh

High Level Design

Energy Management Strategy Design

Battery Management System Design

Simulation

The simulation of powerplant is shown below:

Simulator of the overall system including the energy management system and battery management system:

Result & Discussion

Performance of Energy Management Strategy

The performance of the PCU was compared with Rule-based strategy in terms of total hydrogen fuel consumption, battery SoC.

Predetermined rules set by the team

Power demand	SoC battery	Condition	Current command, A
Negative	SoC < 40	Regenerative braking	0
Negative	40 < SoC < 60	Regenerative braking	0
Negative	SoC > 60	Regenerative braking	0
Zero	SoC < 40	Fuel cell charges the battery	3
Zero	40 < SoC < 60	Fuel cell charges the battery	2
Zero	SoC > 60	No power flow	0
Positive	SoC < 40	Fuel cell mode	4 (maximum)
Positive	40 < SoC < 60	Hybrid mode	2
Positive	SoC > 60	Battery mode	0

The MDP strategy consumes more hydrogen fuel at the start to reach the SoC reference faster compared to rule-based strategy. Then it will maintain the SoC at the reference which is 50%. Using the same driving cycle, the total fuel consumption for MDP strategy is lower than rule-based strategy.

Performance of Battery Management System

The analyse the performance of the our Battery Management Strategy, we compared the estimation SoC by Kalman Filter with real SoC reading from the battery model. The estimation curve has small value of deviation with the real SoC reading. This can ensure the control action determined by the PCU is accurate and correct.

Conclusion & Future Work

The controller was developed by implementing a Markov Decision Process as the strategy. The Battery Management System was introduced the application of Extended Kalman Filter. The fully functional simulator was developed in Simulink to analyse the performance of the controller and the Battery Management System. This proposed strategy is accepted to continue its development by implementing it to the actual model of Fuel Cell Hybrid Vehicle. This strategy can be improved more by using online optimisation problem solving which can be more robust compared to offline.

Reference

[1] A. L. Dicks, D. A. J. Rand, and J. Larminie, Fuel cell systems explained. Chichester: Wiley, 2018.

[2] Y. Huang, H. Wang, A. Khajepour, H. He, and J. Ji, “Model predictive control power management strategies for HEVs: A review,” Journal of Power Sources, vol. 341, pp. 91–106, 2017.

[3] K. Simmons, Y. Guezennec, and S. Onori, “Modeling and energy management control design for a fuel cell hybrid passenger bus,” Journal of Power Sources, vol. 246, pp. 736–746, 2014.

[4] D. Shen, “Week 1 Presentation,” in Project introduction, 06-Jun-2019.