Framework for simulation-based simultaneous system optimization for a series hydraulic hybrid vehicle

Figures & data

Figure 1. Simulation-based design optimisation procedure (adapted from Krus 2003).

Figure 2. Basic system layout (simplified).

Figure 3. Efficiency maps for in-line pump ((a) and (b)) and bent-axis motor ((c) and (d)) with displacement settings of 1.0, 0.67 and 0.33.

Figure 4. Pump scaling relationships for component mass and maximum continuous speed as functions of component displacement.

Table 1. Basic vehicle data.

Kerb weight/Load considered	1800 kg/850 kg
Effective front area	1.3 m^2
Effective wheel radius (incl. final drive)	0.1 m
Rolling resistance coefficient	0.02 [–]
Default diesel engine
Maximum torque	367 Nm
Maximum power	130 kW

Table 2. Drive cycle comparison (Barlow et al. 2009, Tutuianu et al. 2013).

Drive cycle	tcycle (s)	xcycle (km)	vmax (km/h)	v̇max (m/s^2)
UDDS	1369	12.0	91.1	1.5
NEDC	1220	11.0	120.0	1.0
WLTP3 (v5)	1800	23.3	131.3	1.6

Table 3. Design parameter limits.

Design Parameter	Unit	Lower Limit	Upper Limit
Pump displacement Dp	10^−6 m^3/rev	25	250
Pump/motor displacement Dpm	10^−6 m^3/rev	25	250
Flywheel inertia JFW	kgm^2	0	1
Maximum engine torque TICE,max	Nm	75	400
Accumulator volume V0,acc	10^−3 m^3	10	100
Upper state-of-charge limit phigh	10^6 Pa	15	45
Lower state-of-charge limit plow	10^6 Pa	12.5	44^a
Target pressure level psplit	10^6 Pa	plow	phigh
Reference flow qref	m^3/s	0	0.05

^a Adjusted to max. (p_high – 5 · 10⁶) Pa.

Figure 5. Distribution of design parameters within design range (relatively) for different drive cycles and cases. Minimum and maximum for each design parameter given as absolute values (p_split is per definition relative).

Figure 6. Bubble plot of engine operating points for Case I, UDDS-optimised design, together with wide open throttle curve (maximum torque), scaled BSFC-map and fuel-consumption-minimal operating points (BSFC_min).

Figure 7. Reference velocity, energy content in system and instantaneous rate of fuel consumption for Case I, UDDS-optimised design during first 400 s of UDDS.

Table 4. Comparison of system’s energy content for non-hybrid (kinetic energy of vehicle and flywheel) and hybrid case (kinetic energy of vehicle and flywheel plus energy content accumulator) for Case I, UDDS-optimised design.

	Mean energy content	Standard deviation
Non-hybrid	1.8 · 10^5 J	2.2 · 10^5 J
Hybrid	4.4 · 10^5 J	1.7 · 10^5 J

Table 5. Optimised vehicle designs’ fuel consumption (g).

Drive cycle	UDDS	NEDC	WLTP3
Case I	814	844	2072
Case II	888	874	2066

Table 6. Comparison of ARVD for different designs and drive cycles.

Case	Drive cycle	Test cycle
		UDDS	NEDC	WLTP3
I	UDDS	(1.0 %)	3.9 % ^a	8.4 % ^a
	NEDC	2.3 %	(1.0 %)	1.7 % ^a
	WLTP3	1.9 %	0.6 %	(1.0 %)
II	UDDS	(1.0 %)	0.6 % ^a	1.5 % ^a
	NEDC	0.7 %	(0.5 %)	0.9 % ^a
	WLTP3	0.8 %	0.4 %	(0.8 %)

^a Pump speed constraint violated

Krus, P., 2003. Simulation based optimisation for system design. In: Proceedings of the 14th international conference on engineering design, 19–21 August, Stockholm, Sweden. Glasgow: Design Society.

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Barlow, T.J., et al., 2009. A reference book of driving cycles for use in the measurements of road vehicle emissions. Crowthorne, Berkshire, UK: Transport Research Laboratory, Project Report PPR354.

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Tutuianu, M., et al., 2013. Development of a World-wide Worldwide harmonized Light duty driving Test Cycle (WLTC). Technical Report GRPE-68-03, UN/ECE/WP.29/GRPE/WLTP-IG, DHC subgroup. Available from: https://www.unece.org/fileadmin/DAM/trans/doc/2013/wp29grpe/GRPE-67-03.pdf [Accessed 10 October 2018].

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