Time-Variant Online Auto-Tuned PI Controller Using PSO Algorithm for High Accuracy Dual Active Bridge DC-DC Converter

Electric vehicles (EVs) are expected to take over the transportation and mobility market over traditional internal combustion engine (ICE) vehicles soon. The internal power demands of EVs are expected to increase. The reason for this is to achieve a longer driving range for the EV and to provide the required power for the low-voltage (LV) network auxiliary loads. To illustrate, there are extra added sensors, cameras, and small actuating motors, especially for future autonomous vehicles. Therefore, a new electrical/electronic (E/E) architecture is required to convert the high-voltage (HV) traction battery voltage (e.g., 320–800 V DC) to the standard LV levels with high current ratings of 5 kW and more. This HV-LV DC-DC converter is known in the literature as an auxiliary power module (APM). The standard LV rails in an EV are the 12 V/24 V rail to supply for an instant the EV’s lighting and electronic control units (ECUs), while the 48 V rail is required for propulsive loads, such as air compressors and electric power steering systems. Furthermore, in a few applications, this converter is responsible for voltage upwards to support the start of a hybrid vehicle or emergency backup power handling, which requires bidirectional capability. Therefore, in this paper, possible APM topologies for EV applications are presented. In line with this, the main standards and safety requirements of the APMs are presented. Detailed quantitative and qualitative comparisons between topologies and their associated control schemes are discussed. In addition, the placement of the APM in the EV cooling cycle has been investigated and demonstrated. Finally, the industrial trends and future research targets for the APM in automotive applications are outlined.

show abstract

Power Electronics Converters for Electric Vehicle Auxiliaries: State of the Art and Future Trends

Kotb

Chakraborty

Tran

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter

et al. 2023

View full text Add to dashboard Cite

<abstract> Electric vehicles (EVs) are an emerging technology that contribute to reducing air pollution. This paper presents the development of a 200 kW DC charger for the vehicle to grid (V2G) application. The bidirectional dual active bridge (DAB) converter was the preferred fit for a high-power DC-DC conversion due its attractive features. A particle swarm optimization (PSO) algorithm was used to online auto-tune the optimal <italic>KP</italic> and <italic>KI</italic> value with minimize error voltage. Then, by concerning the controller with fixed gains have limitation in response during dynamic change, the PSO was improved to allow re-tuning and update the new <italic>KP</italic> and <italic>KI</italic> upon step changes or disturbances through a time-variant approach. The proposed controller, online auto-tuned PI using PSO with re-tuning (OPSO-PI-RT) and one-time (OPSO-PI-OT) execution were compared under desired output voltage step changes and load step changes in terms of steady-state error and dynamic performance. The OPSO-PI-RT method was a superior controller with 98.16% accuracy and faster controller with 85.28 s-1 average speed compared to OPSO-PI-OT using controller hardware-in-the-loop (CHIL) approach. </abstract>

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Time-Variant Online Auto-Tuned PI Controller Using PSO Algorithm for High Accuracy Dual Active Bridge DC-DC Converter

Cited by 2 publications

References 28 publications

Power Electronics Converters for Electric Vehicle Auxiliaries: State of the Art and Future Trends

Power Electronics Converters for Electric Vehicle Auxiliaries: State of the Art and Future Trends

Adaptive online auto-tuning using Particle Swarm optimized PI controller with time-variant approach for high accuracy and speed in Dual Active Bridge converter

Contact Info

Product

Resources

About